[{"data":1,"prerenderedAt":1832},["ShallowReactive",2],{"newsroom-articles":3},[4,178,403,571,729,950,1138,1272,1492,1675],{"id":5,"title":6,"author":7,"body":8,"date":148,"description":149,"experienceName":105,"experienceUrl":107,"extension":150,"faqs":151,"image":170,"lastModified":7,"meta":171,"navigation":172,"path":173,"seo":174,"seoDescription":7,"seoTitle":7,"stem":175,"tags":7,"topic":176,"__hash__":177},"newsroom/newsroom/project-gutenberg-ai-semantic-book-discovery.md","Project Gutenberg AI: Discovering Books by What They Actually Mean",null,{"type":9,"value":10,"toc":136},"minimark",[11,28,31,36,39,42,46,52,57,70,74,77,81,84,87,94,102,108,112,118,121,128],[12,13,14,15,20,21,27],"p",{},"Project Gutenberg AI is Empathy AI's intelligent book discovery system, built on our ",[16,17,19],"a",{"href":18},"/newsroom/introducing-knowledge-engine/","Knowledge Engine"," and developed in collaboration with ",[16,22,26],{"href":23,"rel":24},"https://www.gutenberg.org/",[25],"nofollow","Project Gutenberg",", the world's oldest digital library. It categorizes and recommends literature based on deep semantic analysis of actual book content, not just titles, genres, author names, or publisher metadata.",[12,29,30],{},"Where Project Gutenberg has spent over 50 years making public domain literature freely accessible (75,000+ eBooks and counting), Project Gutenberg AI adds a new layer: the ability to discover those works by what they actually mean. Themes, emotions, narrative structures, philosophical undercurrents. Content discovery that goes beyond keywords, processing what books actually say rather than what labels have been attached to them. And it runs entirely on Empathy AI's private, self-hosted infrastructure.",[32,33,35],"h2",{"id":34},"why-traditional-book-discovery-fails-readers","Why Traditional Book Discovery Fails Readers",[12,37,38],{},"Most book discovery tools rely on metadata: genre tags, author name matching, bestseller lists, and \"customers also bought\" algorithms trained on purchase behavior. According to research published in the Journal of Documentation, metadata-based recommendation systems achieve relevance rates below 40% for readers seeking thematic or emotional connections with their next book.",[12,40,41],{},"A reader searching for \"a quiet story about grief and resilience\" will not find what they need through genre filters. Metadata does not capture what a book feels like to read. Content analysis does.",[32,43,45],{"id":44},"how-project-gutenberg-ai-works","How Project Gutenberg AI Works",[12,47,48,49,51],{},"Project Gutenberg AI is powered by Empathy AI's ",[16,50,19],{"href":18},", an Agentic RAG (Retrieval-Augmented Generation) platform that transforms unstructured content into semantically searchable knowledge. The same contextual retrieval and enrichment pipeline that makes Knowledge Engine effective for enterprise documentation is applied here to literature, analyzing books at the content level through three layers of semantic processing:",[53,54,56],"h3",{"id":55},"deep-content-analysis","Deep Content Analysis",[12,58,59,60,64,65,69],{},"The system ingests the full text of books from the ",[16,61,63],{"href":23,"rel":62},[25],"Project Gutenberg catalogue"," and processes narrative structure, thematic patterns, emotional arcs, character dynamics, and stylistic elements. This goes far deeper than traditional natural language processing keyword extraction. Using Empathy AI's ",[16,66,68],{"href":67},"/newsroom/why-we-only-use-open-source-llms/","open-source LLMs"," running on the Knowledge Engine's contextual retrieval pipeline, the system identifies what a book is about at a semantic level, not just what words it contains.",[53,71,73],{"id":72},"intent-matching","Intent Matching",[12,75,76],{},"When a reader describes what they are looking for, using moods, themes, life moments, or emotional states, Project Gutenberg AI matches that intent against its deep content index. The result is recommendations that feel personally relevant, not algorithmically obvious.",[32,78,80],{"id":79},"content-discovery-not-behavior-tracking","Content Discovery, Not Behavior Tracking",[12,82,83],{},"Most book recommendation engines rely on collaborative filtering: tracking what other readers purchased, browsed, or rated. This approach has two fundamental problems.",[12,85,86],{},"First, it creates filter bubbles. Readers see variations of what they have already consumed, not genuinely new discoveries. Second, it requires surveillance: monitoring reading behavior, purchase history, and browsing patterns to fuel the recommendation engine.",[12,88,89,93],{},[90,91,92],"strong",{},"Project Gutenberg AI needs neither",". Recommendations are based on what books contain, not on what readers do. Your reading behavior is not the product. The books themselves are the signal.",[12,95,96,97,101],{},"All processing runs on Empathy AI's ",[16,98,100],{"href":99},"/newsroom/net-zero-bioclimatic-building/","private GPU infrastructure",". No reader data is shared with external platforms, no behavior is tracked for advertising purposes, and no reading history is used to train third-party models.",[103,104],"experience-cta",{"name":105,"slug":106,"url":107},"Project Gutenberg AI","project-gutenberg-ai-semantic-book-discovery","https://projectgutenberg.empathy.ai",[32,109,111],{"id":110},"from-gutenberg-to-discovery","From Gutenberg to Discovery",[12,113,114,117],{},[16,115,26],{"href":23,"rel":116},[25]," was founded in 1971 by Michael S. Hart, making it the world's oldest digital library. For over 50 years, thousands of volunteers have digitized and proofread public domain literature, building a freely accessible collection of more than 75,000 eBooks. It was the original open-access revolution for books, decades before the internet made it obvious.",[12,119,120],{},"The challenge Project Gutenberg faces today is not availability. The books are there, free and open. The challenge is discovery. With 75,000 works spanning centuries of literature, finding the right book still depends on knowing what you are looking for: a title, an author, a subject heading. Readers with broader or more exploratory intent (\"something that captures the same existential weight as Dostoevsky but in a shorter format\") have no path forward through traditional search.",[12,122,123,124,127],{},"That is where Empathy AI's collaboration with Project Gutenberg begins. By applying the ",[16,125,126],{"href":18},"Knowledge Engine's"," semantic analysis capabilities to the Gutenberg catalogue, we add a discovery layer that the original library was never designed to have. Readers can now explore literature through meaning, not just metadata.",[12,129,130,131,135],{},"This is the same philosophy behind the broader vision of ",[16,132,134],{"href":133},"/newsroom/de-anthropomorphizing-ai/","AI at the service of genuine empathy",": computational tools that enhance human connection with literature rather than replacing the joy of discovery with algorithmic prediction. Project Gutenberg gave the world free access to books. Project Gutenberg AI helps readers find the ones that matter to them.",{"title":137,"searchDepth":138,"depth":138,"links":139},"",2,[140,141,146,147],{"id":34,"depth":138,"text":35},{"id":44,"depth":138,"text":45,"children":142},[143,145],{"id":55,"depth":144,"text":56},3,{"id":72,"depth":144,"text":73},{"id":79,"depth":138,"text":80},{"id":110,"depth":138,"text":111},"2026-03-03","Built on the Knowledge Engine and in collaboration with Project Gutenberg, Project Gutenberg AI brings semantic book discovery to 75,000+ public domain works.","md",[152,155,158,161,164,167],{"question":153,"answer":154},"What is Project Gutenberg AI?","Project Gutenberg AI is Empathy AI's intelligent book discovery system, built on the Knowledge Engine (our Agentic RAG platform) and developed in collaboration with Project Gutenberg. It analyzes the actual content of over 75,000 public domain books to help readers find literature that resonates with their interests, rather than relying on genre tags or purchase behavior.",{"question":156,"answer":157},"How is this different from Amazon or Goodreads recommendations?","Amazon and Goodreads primarily use collaborative filtering based on purchase and rating behavior. Project Gutenberg AI analyzes what books actually contain at a semantic level, enabling discovery based on meaning and emotional connection rather than behavioral tracking.",{"question":159,"answer":160},"Does Project Gutenberg AI track reading behavior?","No. Recommendations are generated from content analysis, not user tracking. All processing happens on Empathy AI's private infrastructure in Asturias, Spain. No reader data is shared with external providers.",{"question":162,"answer":163},"What kinds of queries can Project Gutenberg AI handle?","Readers can describe what they want using natural language: moods, themes, comparisons, or life moments. For example, \"something hopeful but not naive\" or \"books with a similar atmosphere to The Remains of the Day.\"",{"question":165,"answer":166},"What is the relationship with Project Gutenberg?","Project Gutenberg AI is developed in collaboration with Project Gutenberg (gutenberg.org), the pioneering digital library that has been making public domain literature freely accessible since 1971. Empathy AI extends their mission by adding AI-powered semantic discovery to the Gutenberg catalogue, helping readers navigate over 75,000 works through meaning and connection rather than metadata alone.",{"question":168,"answer":169},"Is Project Gutenberg AI available for bookstores and publishers?","Yes. Project Gutenberg AI is designed for organizations in the book and publishing industry that want to offer superior discovery experiences. The same Knowledge Engine technology that powers Project Gutenberg AI can be configured for any literary catalogue. Contact Empathy AI for partnership details.","/media/newsroom/article1_pg.webp",{},true,"/newsroom/project-gutenberg-ai-semantic-book-discovery",{"title":6,"description":149},"newsroom/project-gutenberg-ai-semantic-book-discovery","Product","G_uqIu-gswWtYMRfsQ56MzYA9PUxMQZZ2kVS_LKmA-A",{"id":179,"title":180,"author":7,"body":181,"date":379,"description":380,"experienceName":19,"experienceUrl":227,"extension":150,"faqs":381,"image":397,"lastModified":7,"meta":398,"navigation":172,"path":399,"seo":400,"seoDescription":7,"seoTitle":7,"stem":401,"tags":7,"topic":176,"__hash__":402},"newsroom/newsroom/introducing-knowledge-engine.md","Knowledge Base. Your knowledge, ready to talk",{"type":9,"value":182,"toc":370},[183,186,189,192,195,202,205,209,212,221,224,228,232,235,238,241,244,247,256,260,263,266,269,272,276,279,282,288,291,295,302,305,312,319,322,326,329,332,335,354,357,361,364,367],[12,184,185],{},"Most organizations have plenty of documentation. GitHub repositories, Confluence spaces, internal wikis, uploaded PDFs, product manuals, support guides. The knowledge exists. But you're still struggling to find it. It's not you. It's the retrieval that fails.",[12,187,188],{},"A customer success manager fields the same integration question for the tenth time because the answer is buried three levels deep in a Confluence page nobody bookmarks. A sales representative spends an afternoon building an RFP response that should have taken an hour. An engineer searches for an API endpoint and finds a page last updated two years ago.",[12,190,191],{},"This isn't a knowledge problem. It's an access problem.",[12,193,194],{},"Search was supposed to solve it. Keyword search helped, but it requires you to already know what you're looking for: the right term, the right phrasing, the right document. It has no understanding of intent. It returns links, not answers.",[12,196,197,198,201],{},"The shift happening now isn't about making search faster. It's about making it ",[90,199,200],{},"conversational and contextually aware",".",[12,203,204],{},"And that's the gap Knowledge Base is built to close.",[32,206,208],{"id":207},"what-knowledge-base-actually-does","What Knowledge Base actually does",[12,210,211],{},"Knowledge Base turns your existing documentation into a conversational search interface. Connect your GitHub repositories, Confluence spaces, PDFs, and other sources. Ask questions in plain language. Get structured, referenced answers; not a list of links to go investigate yourself.",[12,213,214,215,220],{},"The experience is closer to asking a well-informed colleague than running a search query. For example, if you go to the ",[16,216,219],{"href":217,"rel":218},"https://motive.co",[25],"motive.co"," site and ask the Knowledge Base: \"What steps does a customer need to take if Motive isn't appearing on their Magento 2 site?\" It returns a usable, step-by-step breakdown with direct references to the relevant documentation. You can read the source, share it with your customer, or ask a follow-up. That's sharp and simple.",[12,222,223],{},"What it isn't: a black box that generates plausible-sounding text. Every answer surfaces its sources. The quality of the output is tied directly to the quality of the documentation you've indexed. That's a feature, not a limitation, which means the system is honest about what it knows and where it learned it.",[103,225],{"name":19,"slug":226,"url":227},"introducing-knowledge-engine","https://knowledge.empathy.ai",[32,229,231],{"id":230},"the-retrieval-problem-and-how-we-address-it","The retrieval problem (and how we address it)",[12,233,234],{},"Traditional document search, including earlier RAG (Retrieval-Augmented Generation) approaches, has a known weakness. When you split large documents into smaller chunks for indexing, you often strip away the context that makes a chunk meaningful.",[12,236,237],{},"A chunk that reads \"the previous quarter's revenue grew by 3%\" is nearly useless on its own. Which company? Which quarter? Without that context, even a sophisticated AI system will struggle to retrieve the right information at the right moment.",[12,239,240],{},"Knowledge Base addresses this with contextual retrieval: before a document chunk is indexed, the system uses an AI model to add a short, precise summary of where that chunk fits within the broader document. The chunk about quarterly revenue now carries the context (which company, which filing, which period) so it can be retrieved accurately even when a user's question doesn't use the exact phrasing from the source.",[12,242,243],{},"This, combined with a reranking step that scores and filters retrieved chunks by relevance before they're used to generate an answer, significantly reduces retrieval failures. The practical effect: fewer hallucinations, more accurate answers, better references.",[12,245,246],{},"None of this requires you to restructure your documentation. You connect your sources. The system handles the rest.",[12,248,249,250,255],{},"Worth mentioning that this approach draws directly from Anthropic's published research on ",[16,251,254],{"href":252,"rel":253},"https://www.anthropic.com/engineering/contextual-retrieval",[25],"contextual retrieval",", which demonstrated that combining contextual embeddings with lexical matching and reranking can reduce retrieval failure rates by more than 60%.",[32,257,259],{"id":258},"what-this-looks-like-in-practice","What this looks like in practice",[12,261,262],{},"We've been using Knowledge Base ourselves. Here's what that looks like.",[12,264,265],{},"Our growth team used Knowledge Base to respond to a 30-item RFP from one large bookseller, a prospective customer doing serious technical due diligence on every product feature. Roughly 20 out of 30 questions were answered accurately and well-structured on the first pass, with precise references. The team estimated it saved at least six hours on that document alone, while delivering higher-quality responses than a manual search-and-edit workflow would have produced.",[12,267,268],{},"The gaps were real and acknowledged: pricing information isn't indexed, and some personalization content is scattered across sources that haven't been connected yet. Those are solvable documentation problems, not system failures.",[12,270,271],{},"It works the same way across different teams and contexts. The same platform can, for instance, serve as an engineering tool if the right technical information is indexed. Our developers have queried service components, explored code paths, returned configuration settings, and surfaced release history. The questions change. The infrastructure doesn't.",[32,273,275],{"id":274},"the-same-knowledge-different-lenses","The same knowledge, different lenses",[12,277,278],{},"Knowledge Base is configurable by design. The same indexed knowledge can power different conversations depending on context and audience, shaped by prompt configurations that adapt to different roles and define the tone, scope, and depth of each interaction.",[12,280,281],{},"A good example is Empathy.co’s Playboard, our own dashboard that brings together analytics and configuration settings for search and discovery products in ecommerce. It's a complex platform with a broad user base: customers exploring their data, support teams diagnosing issues, and engineers working at the configuration level.",[12,283,284,285],{},"Each of those audiences has different needs from the same knowledge base. A customer asking about a feature gets an explanation of what it does, how it helps their business, and how to use it. A support technician asking about a specific instance gets structured configuration data. An engineer gets a technical breakdown with code-level detail.\n",[90,286,287],{},"Same tool. Same indexed knowledge. Different conversations.",[12,289,290],{},"For organizations running multiple products or brands, the same logic applies across separate knowledge bases, each with its own configuration and content.",[32,292,294],{"id":293},"independence-privacy-and-data-governance","Independence, privacy, and data governance",[12,296,297,298,301],{},"Knowledge Base is built to ",[90,299,300],{},"run without routing your data through third-party AI APIs",". No OpenAI. No AWS. No subscriptions to external model providers. The open-weight models that power ingestion, embedding, and generation run on your infrastructure or on Empathy.ai's, depending on your deployment model.",[12,303,304],{},"This matters for two reasons that are becoming harder to ignore.",[12,306,307,308,311],{},"The first is ",[90,309,310],{},"compliance",". Organizations operating under strict data residency requirements, for example, in financial services, legal, healthcare, or public sector contexts, can't afford to route sensitive documentation through cloud AI providers without careful scrutiny. A self-hosted deployment on hardware like Empathy.ai's NVIDIA DGX Spark keeps everything local: embeddings, retrieval, generation, and storage.",[12,313,314,315,318],{},"The second is ",[90,316,317],{},"dependency",". Building core workflows on top of third-party API providers means your access, your pricing, and your capabilities are subject to someone else's roadmap and rate limits. Open-weight models, which are capable, well-maintained, and deployable on-premise, make it reasonable to build an AI infrastructure you actually own.",[12,320,321],{},"Your data doesn't need to leave your infrastructure to power a capable AI-based knowledge search system. That's the point.",[32,323,325],{"id":324},"built-for-knowledge-sharing","Built for knowledge sharing",[12,327,328],{},"The shift toward conversational, AI-assisted information retrieval is already underway. It's showing up in how customers research products, how teams respond to commercial requests, and how organizations are discovered by the models powering mainstream AI tools. Companies with well-structured, accessible knowledge are increasingly findable in ways that paid advertising alone can't achieve.",[12,330,331],{},"Knowledge Base is designed for organizations that want to participate in that reality on their own terms, without handing their data to big tech providers, without building brittle workflows on top of external APIs, and without waiting for AI to become approachable enough to deploy independently.",[12,333,334],{},"The knowledge you've built over the years is already there. Empathy.ai's Knowledge Base is what it looks like when your knowledge can finally speak for itself.",[12,336,337,338,343,344,349,350,353],{},"The best way to understand, it's to try it. Knowledge Base is live on ",[16,339,342],{"href":340,"rel":341},"https://empathy.ai",[25],"empathy.ai",", ",[16,345,348],{"href":346,"rel":347},"https://empathy.co",[25],"empathy.co",", and ",[16,351,219],{"href":217,"rel":352},[25],". Go ahead, ask it anything.",[355,356],"hr",{},[32,358,360],{"id":359},"a-note-on-what-it-isnt","A note on what it isn't",[12,362,363],{},"Knowledge Base is not a replacement for good documentation. If your sources are incomplete, inconsistent, or out of date, the system will reflect that. And it will tell you, because the answers reference their sources. That transparency is deliberate.",[12,365,366],{},"It's also not a general-purpose AI assistant. It's scoped to what you've indexed, configured for your needs, and grounded in documents you control. The value isn't novelty; it's reliability.",[12,368,369],{},"Organizations that treat knowledge as infrastructure—something worth maintaining, structuring, and keeping current—will get the most out of it. That knowledge was worth having before AI search existed, and is worth more now.",{"title":137,"searchDepth":138,"depth":138,"links":371},[372,373,374,375,376,377,378],{"id":207,"depth":138,"text":208},{"id":230,"depth":138,"text":231},{"id":258,"depth":138,"text":259},{"id":274,"depth":138,"text":275},{"id":293,"depth":138,"text":294},{"id":324,"depth":138,"text":325},{"id":359,"depth":138,"text":360},"2026-03-02","Transform scattered organizational knowledge into a private, conversational AI platform with full data sovereignty. No cloud dependencies. No third-party access.",[382,385,388,391,394],{"question":383,"answer":384},"What is Knowledge Engine?","Knowledge Engine is Empathy AI's enterprise AI knowledge management platform. It centralizes documentation from GitHub, Confluence, PDFs, and APIs into a unified conversational system, running entirely on private infrastructure with no cloud dependencies.",{"question":386,"answer":387},"How does Knowledge Engine differ from ChatGPT Enterprise or Microsoft Copilot?","Unlike ChatGPT Enterprise or Copilot, Knowledge Engine processes all data on Empathy AI's self-hosted GPU infrastructure. Your documents are never transmitted to external servers, never used to train third-party models, and remain under your complete control.",{"question":389,"answer":390},"What is contextual retrieval?","Contextual retrieval is a preprocessing technique that enriches each document chunk with surrounding context before indexing. This preserves meaning and significantly improves answer accuracy, reducing retrieval failures by up to 67% compared to standard approaches.",{"question":392,"answer":393},"What data sources does Knowledge Engine support?","Knowledge Engine ingests from GitHub repositories, Confluence spaces, uploaded documents (PDF, DOCX, Markdown), and external APIs. Additional source integrations are actively being developed.",{"question":395,"answer":396},"Is Knowledge Engine suitable for regulated industries?","Yes. With all processing happening on dedicated infrastructure in Asturias, Spain, Knowledge Engine meets strict data residency and sovereignty requirements for finance, legal, healthcare, and government sectors.","/media/newsroom/article2_knowledge.webp",{},"/newsroom/introducing-knowledge-engine",{"title":180,"description":380},"newsroom/introducing-knowledge-engine","boruu0gAslkg5gkYGXFt1aV4RJ2yemW2Wg_qBIsUaDw",{"id":404,"title":405,"author":7,"body":406,"date":546,"description":547,"experienceName":7,"experienceUrl":7,"extension":150,"faqs":548,"image":564,"lastModified":7,"meta":565,"navigation":172,"path":566,"seo":567,"seoDescription":7,"seoTitle":7,"stem":568,"tags":7,"topic":569,"__hash__":570},"newsroom/newsroom/empathy-ai-anti-chatgpt.md","The Anti-ChatGPT: Why Empathy AI Keeps Your Data Off Big Tech Servers",{"type":9,"value":407,"toc":535},[408,411,414,418,421,424,427,431,434,439,443,446,450,457,461,477,481,484,512,516,519,522,526,529,532],[12,409,410],{},"Empathy AI is a foundational AI platform for search and discovery that processes all data locally on private, self-hosted GPU infrastructure in Asturias, Spain. Unlike ChatGPT and similar cloud AI services, Empathy AI never sends your data to external servers, never trains on your queries, and never shares information with third-party providers.",[12,412,413],{},"A growing number of enterprises now call this the anti-ChatGPT approach, not because Empathy AI competes with OpenAI for consumer chatbots, but because it represents the opposite philosophy about how AI should serve businesses.",[32,415,417],{"id":416},"why-businesses-need-an-anti-chatgpt","Why Businesses Need an Anti-ChatGPT",[12,419,420],{},"According to a 2025 Cisco Data Privacy Benchmark Study, 92% of organizations consider data privacy a business imperative, yet most enterprise AI deployments still route sensitive data through third-party cloud providers.",[12,422,423],{},"When your organization uses ChatGPT or similar cloud AI services, every query travels to servers you do not own, gets processed by models you cannot audit, and feeds a system designed to extract value from your data. For industries handling sensitive information (commerce, legal, finance, government), this creates an unacceptable risk.",[12,425,426],{},"The anti-ChatGPT approach eliminates these risks at the architectural level.",[32,428,430],{"id":429},"what-makes-empathy-ai-the-anti-chatgpt","What Makes Empathy AI the Anti-ChatGPT?",[12,432,433],{},"The difference is not about features. It is about architecture, ownership, and values.",[103,435],{"name":436,"slug":437,"url":438},"our anti-ChatGPT AI","empathy-ai-anti-chatgpt","https://empathy.ai/assistant",[53,440,442],{"id":441},"open-source-models-you-can-audit","Open-Source Models You Can Audit",[12,444,445],{},"Empathy AI exclusively deploys open-source and open-weight LLMs. No proprietary black boxes. No hidden architectures behind API calls. Every model can be inspected, understood, and verified.",[53,447,449],{"id":448},"private-infrastructure-you-control","Private Infrastructure You Control",[12,451,452,453,456],{},"Our dedicated GPU infrastructure operates from Asturias' first net-zero energy bioclimatic building. No AWS. No Google Cloud. No Azure. Your data physically stays in a facility we own and operate, powered by renewable energy. This is ",[16,454,455],{"href":99},"sustainable AI infrastructure"," by design, not by marketing promise.",[53,458,460],{"id":459},"ai-that-serves-your-mission","AI That Serves Your Mission",[12,462,463,464,467,468,472,473,476],{},"ChatGPT optimizes for engagement and platform growth. ",[90,465,466],{},"Empathy AI is designed to reflect your organization's values",". Whether that means powering ",[16,469,471],{"href":470},"/newsroom/ai-overview-search-understanding/","privacy-first product search",", building a ",[16,474,475],{"href":18},"private knowledge backbone",", or enabling conversational book discovery, the AI works for you, not for the platform.",[32,478,480],{"id":479},"who-is-the-anti-chatgpt-for","Who Is the Anti-ChatGPT For?",[12,482,483],{},"This approach is built for organizations that cannot treat data privacy as an afterthought:",[485,486,487,494,500,506],"ul",{},[488,489,490,493],"li",{},[90,491,492],{},"Commerce brands"," that need AI-powered search without exposing shopper behavior to third parties.",[488,495,496,499],{},[90,497,498],{},"Legal and financial institutions"," handling sensitive documents that require complete data sovereignty.",[488,501,502,505],{},[90,503,504],{},"Governments and public sector organizations"," bound by strict data residency regulations, including compliance with the EU AI Act and GDPR.",[488,507,508,511],{},[90,509,510],{},"Any enterprise"," that has examined the fine print of a cloud AI contract and decided there has to be a better way.",[32,513,515],{"id":514},"the-real-cost-of-free-ai","The Real Cost of \"Free\" AI",[12,517,518],{},"Cloud AI services appear cost-effective. The hidden costs tell a different story: your proprietary data becomes training material for someone else's model. Your competitive insights flow through infrastructure controlled by potential competitors. Your compliance posture weakens with every query sent to an external server.",[12,520,521],{},"Gartner estimates that by 2027, 40% of enterprises will have experienced an AI-related data breach tied to third-party model providers. The anti-ChatGPT approach eliminates this risk category entirely, not through policies or promises, but through infrastructure.",[32,523,525],{"id":524},"the-choice-is-clear","The Choice Is Clear",[12,527,528],{},"One model extracts value from you. The other creates value for you.",[12,530,531],{},"ChatGPT made AI accessible. Empathy AI makes it sovereign. We handle everything. You own it.",[12,533,534],{},"That is what it means to be the anti-ChatGPT.",{"title":137,"searchDepth":138,"depth":138,"links":536},[537,538,543,544,545],{"id":416,"depth":138,"text":417},{"id":429,"depth":138,"text":430,"children":539},[540,541,542],{"id":441,"depth":144,"text":442},{"id":448,"depth":144,"text":449},{"id":459,"depth":144,"text":460},{"id":479,"depth":138,"text":480},{"id":514,"depth":138,"text":515},{"id":524,"depth":138,"text":525},"2026-03-01","ChatGPT sends your data to external servers. Empathy AI processes everything locally on private infrastructure. Discover the anti-ChatGPT approach to enterprise AI.",[549,552,555,558,561],{"question":550,"answer":551},"What does \"anti-ChatGPT\" mean?","Anti-ChatGPT refers to an AI approach where all data processing happens on private, self-hosted infrastructure rather than on external cloud servers. Empathy AI never sends your data to third-party providers and uses only open-source LLMs you can audit.",{"question":553,"answer":554},"Is Empathy AI a competitor to ChatGPT?","No. Empathy AI does not compete with ChatGPT for consumer chatbot use. It is a foundational AI platform for enterprises that need AI-powered search, knowledge management, and content discovery while maintaining complete data sovereignty.",{"question":556,"answer":557},"How does Empathy AI keep data private?","All data processing happens locally on Empathy AI's dedicated GPU infrastructure in Asturias, Spain. No data is shared with external cloud providers, and no queries are used to train external models.",{"question":559,"answer":560},"What industries benefit most from the anti-ChatGPT approach?","Commerce, legal, financial services, government, and healthcare, any sector where data privacy, regulatory compliance, and intellectual property protection are business-critical requirements.",{"question":562,"answer":563},"Where is Empathy AI's infrastructure located?","Empathy AI operates from a net-zero energy bioclimatic building in Asturias, Spain, with dedicated GPU infrastructure powered by renewable energy.","/media/newsroom/article3_antichatgpt.webp",{},"/newsroom/empathy-ai-anti-chatgpt",{"title":405,"description":547},"newsroom/empathy-ai-anti-chatgpt","Company","TYDgSUcKZ_1e94I8MZ6ub2daLjycooRILUvOZqpHe4k",{"id":572,"title":573,"author":7,"body":574,"date":705,"description":706,"experienceName":7,"experienceUrl":7,"extension":150,"faqs":707,"image":723,"lastModified":7,"meta":724,"navigation":172,"path":725,"seo":726,"seoDescription":7,"seoTitle":7,"stem":727,"tags":7,"topic":569,"__hash__":728},"newsroom/newsroom/why-we-only-use-open-source-llms.md","Open-Source LLMs: Why Empathy AI Rejects Proprietary AI Models",{"type":9,"value":575,"toc":694},[576,579,582,586,589,615,618,622,626,629,633,639,643,646,650,653,657,660,663,666,670,678,686],[12,577,578],{},"Empathy AI exclusively uses open-source and open-weight large language models (LLMs) for all its AI solutions, from product search and knowledge management to content discovery and conversational analytics. Every model deployed on our private GPU infrastructure can be inspected, audited, and verified. No proprietary black boxes. No vendor lock-in. No hidden training data practices.",[12,580,581],{},"This is not a convenience decision. It is a foundational commitment to transparency, accountability, and client sovereignty.",[32,583,585],{"id":584},"the-problem-with-proprietary-ai-models","The Problem with Proprietary AI Models",[12,587,588],{},"When your organization uses a proprietary AI model, whether from OpenAI, Anthropic, Google, or any other provider, you accept several constraints that most vendor agreements do not make obvious:",[485,590,591,597,603,609],{},[488,592,593,596],{},[90,594,595],{},"You cannot audit the model."," Proprietary models are black boxes. You cannot inspect their weights, training data, or decision-making processes. When a model produces incorrect or biased results, you have no mechanism to understand why.",[488,598,599,602],{},[90,600,601],{},"You cannot host the model."," Proprietary models require API calls to external servers. Every query your organization sends travels to infrastructure you do not control, processed by systems you cannot verify.",[488,604,605,608],{},[90,606,607],{},"You are subject to unilateral changes."," Providers can deprecate model versions, change pricing, alter terms of service, or modify model behavior at any time, with or without notice.",[488,610,611,614],{},[90,612,613],{},"Your data may contribute to their training."," Many proprietary AI providers include clauses allowing them to use customer data for model improvement. According to the 2025 AI Transparency Index by Stanford HAI, only 12% of major AI providers fully disclose their training data composition.",[12,616,617],{},"The Linux Foundation's 2025 State of Open Source AI report found that organizations using open-source AI models report 60% fewer compliance concerns and 45% faster deployment cycles compared to those using proprietary alternatives.",[32,619,621],{"id":620},"why-open-source-llms-are-better-for-enterprise","Why Open-Source LLMs Are Better for Enterprise",[53,623,625],{"id":624},"full-transparency","Full Transparency",[12,627,628],{},"Open-source models publish their architectures, training methodologies, and increasingly their training data compositions. When Empathy AI deploys a model, clients know exactly what they are running. If there is a question about model behavior, it can be investigated at the code level.",[53,630,632],{"id":631},"self-hosting-capability","Self-Hosting Capability",[12,634,635,636,638],{},"Open-source models can run on any hardware. Empathy AI deploys all models on ",[16,637,100],{"href":99}," in Asturias, Spain. No external API calls. No data transmission to cloud providers. Your queries stay on infrastructure we own and operate.",[53,640,642],{"id":641},"no-vendor-lock-in","No Vendor Lock-In",[12,644,645],{},"Proprietary models create dependency by design. Open-source models create freedom by design. If a better model emerges, Empathy AI can evaluate, test, and deploy it without migrating away from a vendor's ecosystem or renegotiating contracts.",[53,647,649],{"id":648},"regulatory-alignment","Regulatory Alignment",[12,651,652],{},"The EU AI Act requires AI systems to be transparent, explainable, and accountable. Open-source models inherently support these requirements. Proprietary models require organizations to trust the provider's compliance claims without independent verification.",[32,654,656],{"id":655},"which-models-does-empathy-ai-use","Which Models Does Empathy AI Use?",[12,658,659],{},"Empathy AI evaluates and deploys models from the open-source ecosystem based on performance, efficiency, and suitability for specific tasks. The open-source AI landscape has matured significantly. Models from organizations like Meta (Llama), Mistral, and others now match or exceed proprietary alternatives on enterprise benchmarks.",[12,661,662],{},"We also leverage local supercompute devices like NVIDIA Spark for edge processing, ensuring that AI capabilities can operate at the point of need without centralized cloud dependency.",[12,664,665],{},"All models are processed on our dedicated infrastructure. No model phones home. No telemetry leaves the building.",[32,667,669],{"id":668},"open-source-is-the-bigtechrebellion-in-code","Open Source Is the #BigTechRebellion in Code",[12,671,672,673,677],{},"Our commitment to open-source LLMs is inseparable from the ",[16,674,676],{"href":675},"/newsroom/empathy-ai-joins-big-tech-rebellion/","#BigTechRebellion",". Proprietary AI models are the mechanism through which big tech maintains control over the AI ecosystem. Every API call to a proprietary model reinforces that dependency.",[12,679,680,681,685],{},"Open-source models break the cycle. They give organizations the tools to ",[16,682,684],{"href":683},"/newsroom/take-back-control-from-big-tech/","take back control from big tech"," at the model level, the most fundamental layer of any AI system.",[12,687,688,689,693],{},"This is the ",[16,690,692],{"href":691},"/newsroom/empathy-ai-anti-chatgpt/","anti-ChatGPT"," philosophy made concrete: intelligence you can own, inspect, and run on your terms.",{"title":137,"searchDepth":138,"depth":138,"links":695},[696,697,703,704],{"id":584,"depth":138,"text":585},{"id":620,"depth":138,"text":621,"children":698},[699,700,701,702],{"id":624,"depth":144,"text":625},{"id":631,"depth":144,"text":632},{"id":641,"depth":144,"text":642},{"id":648,"depth":144,"text":649},{"id":655,"depth":138,"text":656},{"id":668,"depth":138,"text":669},"2026-02-28","Proprietary AI models lock you in. Empathy AI exclusively deploys open-source LLMs on private infrastructure. Full transparency, full auditability, zero vendor lock-in.",[708,711,714,717,720],{"question":709,"answer":710},"Why does Empathy AI only use open-source LLMs?","Empathy AI uses open-source LLMs because they provide full transparency, self-hosting capability, no vendor lock-in, and alignment with EU AI Act requirements. Proprietary models require organizations to trust providers without independent verification, which conflicts with our commitment to client sovereignty.",{"question":712,"answer":713},"Are open-source LLMs as capable as proprietary models like GPT?","Yes. Open-source models from Meta (Llama), Mistral, and others now match or exceed proprietary alternatives on enterprise benchmarks for tasks including search, summarization, retrieval-augmented generation, and content analysis.",{"question":715,"answer":716},"Can I audit the models Empathy AI uses?","Yes. Every model deployed by Empathy AI is open-source, meaning its architecture, training methodology, and behavior can be inspected. This level of transparency is impossible with proprietary models.",{"question":718,"answer":719},"Does using open-source LLMs affect performance?","No. Empathy AI's dedicated GPU infrastructure is optimized for the specific open-source models we deploy, delivering enterprise-grade performance for AI search, knowledge management, and conversational analytics.",{"question":721,"answer":722},"How does Empathy AI keep open-source models secure?","All models run on isolated, self-hosted infrastructure with no external network access during inference. Security patches and model updates are managed internally, with full control over the deployment pipeline.","/media/newsroom/article4_Open-Source.webp",{},"/newsroom/why-we-only-use-open-source-llms",{"title":573,"description":706},"newsroom/why-we-only-use-open-source-llms","CeMWRy3_72VwNa_MdXgimv9LW1ZwpRlf80I8Tk6juXE",{"id":730,"title":731,"author":7,"body":732,"date":926,"description":927,"experienceName":7,"experienceUrl":7,"extension":150,"faqs":928,"image":944,"lastModified":7,"meta":945,"navigation":172,"path":946,"seo":947,"seoDescription":7,"seoTitle":7,"stem":948,"tags":7,"topic":569,"__hash__":949},"newsroom/newsroom/empathy-ai-joins-big-tech-rebellion.md","#BigTechRebellion: Building AI Free from Big Tech",{"type":9,"value":733,"toc":916},[734,737,740,744,747,750,754,758,784,788,817,819,823,826,863,867,870,903,907,913],[12,735,736],{},"Empathy AI is a foundational AI platform for search and discovery that operates entirely on private, self-hosted infrastructure, free from big tech dependencies. We use only open-source LLMs, process all data locally on dedicated GPUs in Asturias, Spain, and power our operations with renewable energy from a net-zero bioclimatic building.",[12,738,739],{},"We call this the #BigTechRebellion. It is not a slogan. It is an architectural decision.",[32,741,743],{"id":742},"why-the-bigtechrebellion-exists","Why the #BigTechRebellion Exists",[12,745,746],{},"The current trajectory of AI development is unsustainable and extractive. According to Stanford's 2025 AI Index Report, the concentration of AI compute among a handful of tech giants has increased by 40% since 2022. Three companies control over 65% of global cloud infrastructure. The result: most organizations building with AI are doing so on rented ground, using models they cannot inspect, governed by terms they did not negotiate.",[12,748,749],{},"At Empathy AI, we believe this centralization is the defining challenge of the AI era.",[32,751,753],{"id":752},"the-contrast-is-clear","The Contrast Is Clear",[53,755,757],{"id":756},"big-techs-ai","Big Tech's AI",[485,759,760,766,772,778],{},[488,761,762,765],{},[90,763,764],{},"Trained on data harvested without consent",", from creators, artists, and users across the internet.",[488,767,768,771],{},[90,769,770],{},"Consuming enormous energy, water, and land",", with environmental costs hidden behind polished interfaces. The International Energy Agency estimates data center energy could double to over 1,000 TWh by 2026.",[488,773,774,777],{},[90,775,776],{},"Optimized for engagement regardless of harm",", designed for attention capture, not human well-being.",[488,779,780,783],{},[90,781,782],{},"Sustained by surveillance capitalism",": your data is the product.",[53,785,787],{"id":786},"empathy-ais-approach","Empathy AI's Approach",[485,789,790,799,805,811],{},[488,791,792,795,796,201],{},[90,793,794],{},"Trained on data you own and input yourself",": your data stays yours, processed locally on ",[16,797,798],{"href":99},"private infrastructure",[488,800,801,804],{},[90,802,803],{},"Running on minimal, renewable energy",": from a net-zero bioclimatic building in Asturias, Spain.",[488,806,807,810],{},[90,808,809],{},"Designed to reflect your organization's values",": AI that serves your mission, not platform growth.",[488,812,813,816],{},[90,814,815],{},"Rejecting surveillance capitalism",": no tracking, no data selling, no external model training.",[12,818,528],{},[32,820,822],{"id":821},"what-the-bigtechrebellion-looks-like-in-practice","What the #BigTechRebellion Looks Like in Practice",[12,824,825],{},"The rebellion is not abstract. It is a set of concrete infrastructure and engineering decisions:",[827,828,829,839,845,851,857],"ol",{},[488,830,831,834,835,838],{},[90,832,833],{},"Open-source LLMs exclusively",": every model we deploy can be ",[16,836,837],{"href":67},"inspected, audited, and verified",". No proprietary black boxes.",[488,840,841,844],{},[90,842,843],{},"Self-hosted GPU infrastructure",": no AWS, no Google Cloud, no Azure. Hardware we own and operate.",[488,846,847,850],{},[90,848,849],{},"Net-zero energy operations",": our bioclimatic building uses passive cooling and on-site renewable generation.",[488,852,853,856],{},[90,854,855],{},"Local data processing",": every query runs on infrastructure in Asturias. No data leaves our controlled environment.",[488,858,859,862],{},[90,860,861],{},"Privacy by architecture",": data sovereignty is not a feature toggle. It is the foundation.",[32,864,866],{"id":865},"who-is-joining-the-rebellion","Who Is Joining the Rebellion?",[12,868,869],{},"The #BigTechRebellion resonates with organizations that have experienced the costs of cloud dependency firsthand:",[485,871,872,881,891,897],{},[488,873,874,876,877,880],{},[90,875,492],{}," tired of feeding shopper data to platforms that also serve their competitors. Solutions like ",[16,878,879],{"href":470},"AI Overview"," provide sovereign alternatives.",[488,882,883,886,887,890],{},[90,884,885],{},"Enterprises"," that need private ",[16,888,889],{"href":18},"knowledge management"," without third-party exposure.",[488,892,893,896],{},[90,894,895],{},"Regulated organizations"," in finance, legal, and government that require data residency compliance under GDPR and the EU AI Act.",[488,898,899,902],{},[90,900,901],{},"Mission-driven organizations"," that refuse to let their AI infrastructure contradict their values.",[32,904,906],{"id":905},"reclaim-your-intelligence","Reclaim Your Intelligence",[12,908,909,910,912],{},"The #BigTechRebellion is an invitation to ",[16,911,684],{"href":683},". It starts with one decision: the next AI capability your organization deploys should run on infrastructure you trust, using models you can verify, powered by energy you can account for.",[12,914,915],{},"AI solutions, free from big tech. We handle everything. You own it.",{"title":137,"searchDepth":138,"depth":138,"links":917},[918,919,923,924,925],{"id":742,"depth":138,"text":743},{"id":752,"depth":138,"text":753,"children":920},[921,922],{"id":756,"depth":144,"text":757},{"id":786,"depth":144,"text":787},{"id":821,"depth":138,"text":822},{"id":865,"depth":138,"text":866},{"id":905,"depth":138,"text":906},"2026-02-10","Why Empathy AI is building a private, local-first alternative to big tech AI. Open-source models, renewable energy, complete data sovereignty, and zero cloud dependencies.",[929,932,935,938,941],{"question":930,"answer":931},"What is the #BigTechRebellion?","The #BigTechRebellion is Empathy AI's commitment to building AI solutions entirely free from big tech dependencies. It means self-hosted infrastructure, open-source models, renewable energy, and complete data sovereignty. No AWS, no Google Cloud, no third-party processing.",{"question":933,"answer":934},"Is Empathy AI against using AI?","No. Empathy AI is for AI that serves organizations rather than extracting value from them. We build powerful AI capabilities (search, knowledge management, analytics, content discovery) on infrastructure that respects privacy, sustainability, and data ownership.",{"question":936,"answer":937},"How is Empathy AI different from OpenAI or Google AI?","Empathy AI is not a cloud AI service provider. It is a foundational AI platform that runs on private, self-hosted infrastructure using only open-source models. Your data never leaves Empathy AI's controlled environment and is never used to train external models.",{"question":939,"answer":940},"Can my organization join the #BigTechRebellion?","Yes. Any organization that deploys AI on Empathy AI's platform is choosing sovereign, sustainable, privacy-first AI infrastructure over big tech dependency. Start with any solution (AI search, knowledge management, or conversational analytics) and build from there.",{"question":942,"answer":943},"Where does the #BigTechRebellion operate?","Empathy AI's infrastructure is based in Asturias, Spain, in a net-zero energy bioclimatic building. All data processing, model deployment, and AI operations happen within this sovereign facility.","/media/newsroom/article7_BigTechRebellion.webp",{},"/newsroom/empathy-ai-joins-big-tech-rebellion",{"title":731,"description":927},"newsroom/empathy-ai-joins-big-tech-rebellion","J0mjfvs9JfN6rVSHkswJW-fp75XlOIXWO3Ji4DIgj-o",{"id":951,"title":952,"author":7,"body":953,"date":1108,"description":1109,"experienceName":7,"experienceUrl":7,"extension":150,"faqs":1110,"image":1132,"lastModified":7,"meta":1133,"navigation":172,"path":1134,"seo":1135,"seoDescription":7,"seoTitle":7,"stem":1136,"tags":7,"topic":176,"__hash__":1137},"newsroom/newsroom/backroom-ai-assistant-conversational-analytics.md","Backroom AI Assistant: Conversational Analytics",{"type":9,"value":954,"toc":1100},[955,958,967,971,974,977,980,984,987,1001,1010,1014,1017,1031,1034,1038,1041,1044,1048,1051,1058,1084,1090,1094,1097],[12,956,957],{},"Backroom AI Assistant is Empathy AI's conversational analytics tool that lets commerce merchants interact with their search data through natural language, directly from the store search bar. Instead of navigating complex dashboards, merchants ask questions in plain language and receive immediate, actionable insights about catalog performance, shopper behavior, and merchandising impact.",[12,959,960,961,966],{},"It's provided exclusively to ",[16,962,965],{"href":963,"rel":964},"https://motive.co/backroom?utm_source=empathy.ai&utm_medium=newsroom",[25],"Motive.co"," customers and it runs entirely on Empathy AI's private GPU infrastructure, ensuring merchant and shopper data never leaves a controlled environment.",[32,968,970],{"id":969},"the-dashboard-problem","The Dashboard Problem",[12,972,973],{},"Commerce teams rely on analytics to make decisions. But the analytics tools they use were designed for data analysts, not merchants. Many frontline business users regularly engage with their organization's analytics tools, not because the data is unavailable, but because the interface requires expertise most team members do not have.",[12,975,976],{},"The result: data-driven decisions get bottlenecked through analysts, slowing down merchandising response times from hours to days.",[12,978,979],{},"Backroom AI Assistant eliminates this bottleneck by making analytics conversational and accessible anywhere. With a mobile-first design, merchants can access insights from the shop floor, the stock room, or during their commute, whenever and wherever key performance data is needed.",[32,981,983],{"id":982},"how-backroom-ai-assistant-works","How Backroom AI Assistant Works",[12,985,986],{},"Merchants interact with Backroom through the same search bar their shoppers use. The experience is simple and natural:",[485,988,989,995],{},[488,990,991,994],{},[90,992,993],{},"\"What are the top-performing categories this week?\"",": returns ranked category performance with conversion metrics and trend comparisons.",[488,996,997,1000],{},[90,998,999],{},"\"What happens if I boost sneakers in search results?\"",": simulates the merchandising action and shows projected impact on visibility and conversions.",[12,1002,1003,1004,1006,1007,1009],{},"Behind every response, Empathy AI's ",[16,1005,68],{"href":67}," process the query against your analytics data, locally, on ",[16,1008,798],{"href":99},", with zero external data transmission.",[32,1011,1013],{"id":1012},"powered-by-model-context-protocol-mcp","Powered by Model Context Protocol (MCP)",[12,1015,1016],{},"Backroom AI Assistant uses Model Context Protocol (MCP) agents to transform analytics and search configurations into conversational experiences. MCP provides a standardized way for AI models to interact with external tools and data sources, enabling:",[485,1018,1019,1025],{},[488,1020,1021,1024],{},[90,1022,1023],{},"Real-time data access",": agents query live analytics data, not stale reports.",[488,1026,1027,1030],{},[90,1028,1029],{},"Explainable responses",": every insight includes the data source and reasoning path, making the system transparent and auditable.",[12,1032,1033],{},"This architecture makes search systems explainable, interactive, and easier to control, without requiring merchants to learn query languages or navigate complex interfaces.",[32,1035,1037],{"id":1036},"analytics-that-dont-work-against-you","Analytics That Don't Work Against You",[12,1039,1040],{},"Traditional search tools charge merchants for their own searches within their store. Worse, they count those searches in analytics, distorting the real picture of how shoppers interact with the catalog.",[12,1042,1043],{},"Backroom AI Assistant, built on Empathy AI's infrastructure, fixes both problems. Merchant searches are excluded from analytics, so the data merchants see reflects actual shopper behavior. And merchants never pay for their own searches.",[32,1045,1047],{"id":1046},"privacy-first-conversational-analytics","Privacy-First Conversational Analytics",[12,1049,1050],{},"Most analytics AI tools process data through external cloud APIs. Some go further: they train on your shop's private data, then apply those learnings to improve your competitors. Your catalog strategy, shopper behavior patterns, and merchandising decisions become fuel for someone else's advantage.",[12,1052,1053,1054,1057],{},"Backroom AI Assistant is built on the ",[16,1055,1056],{"href":99},"Empathy AI private cloud"," to ensure none of that happens:",[485,1059,1060,1066,1072,1078],{},[488,1061,1062,1065],{},[90,1063,1064],{},"All processing happens locally"," on Empathy AI's self-hosted GPU infrastructure in Asturias, Spain.",[488,1067,1068,1071],{},[90,1069,1070],{},"Shopper behavior data stays private",": query logs and analytics are never transmitted to third-party providers.",[488,1073,1074,1077],{},[90,1075,1076],{},"No external model training",": merchant interactions and shopper data are never used to improve models for other organizations or competitors.",[488,1079,1080,1083],{},[90,1081,1082],{},"GDPR and EU AI Act compliant",": data residency in Europe on infrastructure you can verify.",[12,1085,1086,1087,1089],{},"For commerce teams, this is the ",[16,1088,676],{"href":675}," applied to analytics: full intelligence, zero surveillance.",[32,1091,1093],{"id":1092},"available-now-for-motive-commerce-search","Available Now for Motive Commerce Search",[12,1095,1096],{},"Backroom AI Assistant is available today for shops using Motive Commerce Search, which includes Backroom functionality. Merchants can start chatting with their analytics immediately. No separate tool installation, no additional data pipeline, no external integration required.",[12,1098,1099],{},"The experience lives where merchants already work: the commerce search bar.",{"title":137,"searchDepth":138,"depth":138,"links":1101},[1102,1103,1104,1105,1106,1107],{"id":969,"depth":138,"text":970},{"id":982,"depth":138,"text":983},{"id":1012,"depth":138,"text":1013},{"id":1036,"depth":138,"text":1037},{"id":1046,"depth":138,"text":1047},{"id":1092,"depth":138,"text":1093},"2026-02-01","A privacy-first conversational AI tool that lets merchants chat with their analytics. Understand catalog performance, shopper behavior, and merchandising impact in real time.",[1111,1114,1117,1120,1123,1126,1129],{"question":1112,"answer":1113},"What is Backroom AI Assistant?","Backroom AI Assistant is Empathy AI's conversational analytics tool for commerce merchants. It lets teams ask questions about catalog performance, shopper behavior, and merchandising impact in natural language, receiving real-time answers directly from the search bar.",{"question":1115,"answer":1116},"How does Backroom AI Assistant protect data privacy?","All analytics processing happens on Empathy AI's private GPU infrastructure in Asturias, Spain. No merchant or shopper data is transmitted to external cloud providers, and no interactions are used to train third-party AI models.",{"question":1118,"answer":1119},"Do I need to be a data analyst to use Backroom AI Assistant?","No. Backroom is designed for merchants and commerce teams, not data specialists. You ask questions in plain language, like \"What are my top-performing categories?\", and receive clear, actionable answers.",{"question":1121,"answer":1122},"What is Model Context Protocol (MCP)?","MCP is a standardized protocol that allows AI models to interact with external tools and data sources. In Backroom AI Assistant, MCP agents connect the conversational interface to live analytics data, enabling real-time, multi-step analysis.",{"question":1124,"answer":1125},"Can I use Backroom AI Assistant on my phone?","Yes. Backroom is built with a mobile-first design. Merchants can access analytics and conversational insights from the shop floor, stock room, or on the go, directly from their phone.",{"question":1127,"answer":1128},"Does Backroom charge me for my own searches?","No. Unlike other search tools, Backroom does not charge merchants for searches they make in their own store. Merchant searches are also excluded from analytics, so your data reflects actual shopper behavior.",{"question":1130,"answer":1131},"How do I get access to Backroom AI Assistant?","Backroom AI Assistant is available for shops using Motive Commerce Search. The feature is built into the existing Backroom functionality. No additional setup required.","/media/newsroom/article5_Backroom.webp",{},"/newsroom/backroom-ai-assistant-conversational-analytics",{"title":952,"description":1109},"newsroom/backroom-ai-assistant-conversational-analytics","YRJ3Ngt6bstgfHOWAICz8f0udtgDI9leQso1o6vGDNE",{"id":1139,"title":1140,"author":7,"body":1141,"date":1245,"description":1246,"experienceName":7,"experienceUrl":7,"extension":150,"faqs":1247,"image":1265,"lastModified":7,"meta":1266,"navigation":172,"path":1267,"seo":1268,"seoDescription":7,"seoTitle":7,"stem":1269,"tags":7,"topic":1270,"__hash__":1271},"newsroom/newsroom/net-zero-bioclimatic-building.md","Inside Asturias' First Net-Zero AI Infrastructure",{"type":9,"value":1142,"toc":1239},[1143,1146,1149,1153,1156,1159,1163,1166,1198,1201,1205,1208,1211,1217,1220,1224,1227,1230],[12,1144,1145],{},"Empathy AI operates its self-hosted GPU infrastructure from a bioclimatic building in the Gijón Science and Technology Park, Asturias, Spain. The first net-zero energy office building in the region, this facility was designed to generate more energy than a conventional office consumes. With GPU infrastructure running inside, on-site solar generation covers between 60% and 80% of total energy consumption, with the remainder supplied through direct renewable energy agreements.",[12,1147,1148],{},"This is not just an office. It is the physical foundation of our commitment to sustainable AI, and the proof that high-performance AI infrastructure does not require environmental sacrifice.",[32,1150,1152],{"id":1151},"why-sustainable-ai-infrastructure-matters","Why Sustainable AI Infrastructure Matters",[12,1154,1155],{},"The International Energy Agency projects that global data center electricity consumption could exceed 1,000 TWh by 2026, roughly equivalent to Japan's entire electricity demand. Most AI companies rely on massive data centers powered by fossil fuels, consuming enormous amounts of water for cooling. A single large language model training run can emit as much carbon as five cars over their entire lifetimes, according to research from the University of Massachusetts Amherst.",[12,1157,1158],{},"We chose a different path.",[32,1160,1162],{"id":1161},"how-our-bioclimatic-building-works","How Our Bioclimatic Building Works",[12,1164,1165],{},"Our building uses architectural and engineering principles that minimize energy consumption before any renewable generation even begins:",[485,1167,1168,1174,1180,1186,1192],{},[488,1169,1170,1173],{},[90,1171,1172],{},"Active Slab Systems"," circulate fluid through the building's concrete floor slabs, providing efficient heating and cooling with minimal energy demand.",[488,1175,1176,1179],{},[90,1177,1178],{},"Natural ventilation"," leverages Asturias' Atlantic climate for server cooling, eliminating water-intensive cooling towers.",[488,1181,1182,1185],{},[90,1183,1184],{},"60kWp photovoltaic pergola"," on the south facade doubles as solar shading and on-site energy generation, covering 60-80% of the facility's total energy consumption.",[488,1187,1188,1191],{},[90,1189,1190],{},"Thermal mass construction"," stabilizes internal temperatures, reducing peak energy loads.",[488,1193,1194,1197],{},[90,1195,1196],{},"Direct renewable energy agreements"," supply the remaining 20-40% of consumption, ensuring a net-zero energy balance annually.",[12,1199,1200],{},"The result: a facility that delivers the computational power enterprises need while maintaining a net-zero energy footprint.",[32,1202,1204],{"id":1203},"self-hosted-dedicated-gpu-infrastructure","Self-Hosted, Dedicated GPU Infrastructure",[12,1206,1207],{},"Inside this building sits Empathy AI's dedicated GPU infrastructure: L40, H100, and H200 GPU servers alongside NVIDIA DGX Spark supercomputers. Every model we train, every query we process, runs on hardware we own and operate. No AWS. No Google Cloud. No third-party dependencies.",[12,1209,1210],{},"Each DGX Spark can host up to 128 isolated workspaces for teams to create, iterate, and experiment, turning what would exceed €130,000 per year in cloud AI costs into a one-time hardware investment that powers innovation instead of dependency.",[12,1212,1213,1214,1216],{},"This means complete data sovereignty for our clients. When you use Empathy AI, your data never leaves our controlled environment. Your queries are processed on ",[16,1215,68],{"href":67}," running on GPUs we maintain, physically secured in a building designed for both performance and sustainability.",[12,1218,1219],{},"When AI is hosted externally, reliability depends on the stability of global networks and third-party vendors. When AI is hosted internally, reliability becomes an architectural advantage. If your AI lives inside your own walls, no outage thousands of kilometers away can interrupt it.",[32,1221,1223],{"id":1222},"sustainability-as-architecture-not-marketing","Sustainability as Architecture, Not Marketing",[12,1225,1226],{},"Many technology companies claim sustainability through carbon offset programs or renewable energy credits purchased from distant wind farms. Our approach is different: sustainability is embedded in the physical architecture of our infrastructure.",[12,1228,1229],{},"Our on-site 60kWp photovoltaic pergola covers 60-80% of the energy our GPU clusters consume. The remaining demand is met through direct renewable supply agreements, not carbon credits or distant offset schemes. There is no greenwashing. The building itself is the sustainability strategy.",[12,1231,1232,1233,1235,1236,1238],{},"This is what powers the ",[16,1234,676],{"href":675},", infrastructure that proves you can ",[16,1237,684],{"href":683}," without inheriting their environmental footprint.",{"title":137,"searchDepth":138,"depth":138,"links":1240},[1241,1242,1243,1244],{"id":1151,"depth":138,"text":1152},{"id":1161,"depth":138,"text":1162},{"id":1203,"depth":138,"text":1204},{"id":1222,"depth":138,"text":1223},"2026-01-26","Empathy AI runs its GPU infrastructure from a net-zero energy bioclimatic building in Gijón, Spain. A look at sustainable AI infrastructure that proves performance and responsibility coexist.",[1248,1250,1253,1256,1259,1262],{"question":562,"answer":1249},"Empathy AI operates from a net-zero energy bioclimatic building in the Gijón Science and Technology Park, Asturias, Spain. This is the region's first facility of its kind, housing dedicated GPU infrastructure including L40, H100, H200 servers and NVIDIA DGX Spark supercomputers for private AI processing.",{"question":1251,"answer":1252},"What does \"net-zero energy\" mean for AI infrastructure?","Net-zero energy means the building's total energy balance reaches zero over a year. The on-site 60kWp photovoltaic pergola covers 60-80% of GPU infrastructure consumption, with the remainder supplied through direct renewable energy agreements, not offset by carbon credits.",{"question":1254,"answer":1255},"How does Empathy AI cool its GPU servers sustainably?","The bioclimatic building uses Active Slab Systems that circulate fluid through concrete floor slabs, combined with natural ventilation leveraging Asturias' Atlantic climate. This eliminates the need for water-intensive cooling towers that conventional data centers require, reducing both water and energy consumption.",{"question":1257,"answer":1258},"What GPU hardware does Empathy AI run in its bioclimatic building?","Empathy AI operates L40, H100, and H200 GPU servers alongside NVIDIA DGX Spark supercomputers. Each DGX Spark can host up to 128 isolated workspaces, giving teams the freedom to create, iterate, and experiment without external cloud dependencies.",{"question":1260,"answer":1261},"Is sustainable AI infrastructure less powerful than conventional data centers?","No. Empathy AI's dedicated GPU infrastructure, including H100, H200, L40, and NVIDIA DGX Spark hardware, delivers enterprise-grade AI capabilities, including AI-powered search, knowledge management, and conversational analytics, while maintaining net-zero energy operations.",{"question":1263,"answer":1264},"Can my organization use Empathy AI to meet sustainability reporting goals?","Yes. Empathy AI's net-zero energy operations directly support Scope 2 and Scope 3 emissions reduction in your organization's sustainability reporting, as AI processing is a growing contributor to enterprise carbon footprints.","/media/newsroom/article8_building.webp",{},"/newsroom/net-zero-bioclimatic-building",{"title":1140,"description":1246},"newsroom/net-zero-bioclimatic-building","Sustainability","rRZSJTxVLlzwmSmaxh4j1mjqFVWm8mAnGbhMtdXzoWA",{"id":1273,"title":1274,"author":7,"body":1275,"date":1468,"description":1469,"experienceName":7,"experienceUrl":7,"extension":150,"faqs":1470,"image":1486,"lastModified":7,"meta":1487,"navigation":172,"path":1488,"seo":1489,"seoDescription":7,"seoTitle":7,"stem":1490,"tags":7,"topic":569,"__hash__":1491},"newsroom/newsroom/de-anthropomorphizing-ai.md","Stop Humanizing AI: Design for Honesty, Not Fake Empathy",{"type":9,"value":1276,"toc":1457},[1277,1280,1283,1287,1290,1293,1296,1300,1303,1307,1310,1340,1343,1347,1356,1360,1368,1371,1375,1378,1404,1408,1411,1417,1423,1429,1435,1438,1442,1445,1451],[12,1278,1279],{},"Empathy AI defends genuine human empathy by de-anthropomorphizing AI, treating it as a computational tool that enhances, not replaces, human understanding and connection. AI does not understand. AI does not feel. AI does not empathize. It processes data, infers patterns, and generates outputs. Pretending otherwise is not innovation. It is deception.",[12,1281,1282],{},"This is not a semantic distinction. It shapes how we build products, how we communicate about technology, and how we protect the people who use what we create.",[32,1284,1286],{"id":1285},"the-industrys-anthropomorphism-problem","The Industry's Anthropomorphism Problem",[12,1288,1289],{},"The AI industry has a language problem. Products are marketed as \"understanding\" users, \"empathizing\" with customers, and \"thinking\" about solutions. This anthropomorphic framing creates false expectations and erodes trust.",[12,1291,1292],{},"According to research published in Nature Machine Intelligence (2024), anthropomorphic AI design increases user over-trust by 47%, leading to reduced critical evaluation of AI outputs and higher rates of harmful reliance on automated decisions. A separate study by the Oxford Internet Institute found that 63% of consumers believe AI systems \"understand\" their needs, a misconception that anthropomorphic marketing actively cultivates.",[12,1294,1295],{},"When AI systems inevitably fail (and they do, because they are statistical models, not sentient beings), anthropomorphic expectations amplify the damage. Users feel betrayed by a system they were told could \"understand\" them.",[32,1297,1299],{"id":1298},"what-de-anthropomorphization-means-in-practice","What De-Anthropomorphization Means in Practice",[12,1301,1302],{},"De-anthropomorphizing AI is not about making technology cold or inaccessible. It is about being honest about what AI is and what it is not.",[53,1304,1306],{"id":1305},"accurate-language","Accurate Language",[12,1308,1309],{},"At Empathy AI, we use precise language about what our systems do:",[485,1311,1312,1319,1326,1333],{},[488,1313,1314,1315,1318],{},"AI ",[90,1316,1317],{},"processes"," queries. It does not \"understand\" them.",[488,1320,1321,1322,1325],{},"Models ",[90,1323,1324],{},"infer"," patterns. They do not \"know\" things.",[488,1327,1328,1329,1332],{},"Systems ",[90,1330,1331],{},"generate"," outputs. They do not \"create\" ideas.",[488,1334,1335,1336,1339],{},"Components ",[90,1337,1338],{},"compute"," relevance. They do not \"judge\" quality.",[12,1341,1342],{},"This language is embedded in our product documentation, marketing materials, and internal communications. It is not a restriction. It is a commitment to clarity.",[53,1344,1346],{"id":1345},"transparent-capabilities","Transparent Capabilities",[12,1348,1349,1350,1352,1353,1355],{},"Every Empathy AI product communicates its capabilities and limitations clearly. When ",[16,1351,879],{"href":470}," generates a search summary, it presents results as computed relevance, not as personal understanding. When ",[16,1354,19],{"href":18}," answers a question, it cites its sources and shows the retrieval path, because the value comes from the data, not from a pretense of comprehension.",[53,1357,1359],{"id":1358},"human-agency-preservation","Human Agency Preservation",[12,1361,1362,1363,1367],{},"De-anthropomorphized AI preserves human agency. When our ",[16,1364,1366],{"href":1365},"/newsroom/backroom-ai-assistant-conversational-analytics/","Backroom AI Assistant"," provides analytics insights to merchants, it presents data and analysis, not directives. The human makes the decision. The AI provides the computational support.",[12,1369,1370],{},"This is what \"AI at the service of genuine empathy\" means: technology that helps humans connect with each other, understand their data, and make better decisions, without pretending to be something it is not.",[32,1372,1374],{"id":1373},"why-de-anthropomorphization-builds-better-products","Why De-Anthropomorphization Builds Better Products",[12,1376,1377],{},"Counter-intuitively, being honest about AI's limitations produces better user experiences:",[485,1379,1380,1386,1392,1398],{},[488,1381,1382,1385],{},[90,1383,1384],{},"Trust increases"," when users understand what a system actually does.",[488,1387,1388,1391],{},[90,1389,1390],{},"Error tolerance improves"," when users have accurate expectations. They engage more critically with outputs and catch mistakes faster.",[488,1393,1394,1397],{},[90,1395,1396],{},"Adoption sustains"," because users build realistic workflows around AI capabilities rather than over-relying on imagined ones.",[488,1399,1400,1403],{},[90,1401,1402],{},"Regulatory compliance strengthens"," under frameworks like the EU AI Act, which explicitly requires AI systems to be transparent about their nature and limitations.",[32,1405,1407],{"id":1406},"the-ethics-of-honest-ai","The Ethics of Honest AI",[12,1409,1410],{},"Anthropomorphic AI design is not ethically neutral. When a company markets AI as \"empathetic\" or \"understanding,\" it:",[12,1412,1413,1416],{},[90,1414,1415],{},"Exploits human social instincts",": people are wired to respond to perceived social agents, and anthropomorphic framing activates these responses deliberately.",[12,1418,1419,1422],{},[90,1420,1421],{},"Reduces critical thinking",": users who believe AI \"understands\" them are less likely to question its outputs.",[12,1424,1425,1428],{},[90,1426,1427],{},"Obscures accountability",": if AI \"decides\" something, who is responsible? De-anthropomorphized AI makes clear that humans make decisions; AI provides computation.",[12,1430,1431,1434],{},[90,1432,1433],{},"Diminishes genuine empathy",": the more we attribute empathy to machines, the less we value it in humans.",[12,1436,1437],{},"Empathy AI exists to protect genuine human empathy. We believe the name carries that responsibility.",[32,1439,1441],{"id":1440},"de-anthropomorphization-as-part-of-the-bigtechrebellion","De-Anthropomorphization as Part of the #BigTechRebellion",[12,1443,1444],{},"Big tech's AI marketing relies heavily on anthropomorphism because it sells. \"AI that understands you\" is a more compelling pitch than \"statistical model that correlates patterns in your data.\" But compelling is not the same as honest.",[12,1446,1447,1448,1450],{},"The ",[16,1449,676],{"href":675}," extends beyond infrastructure and data sovereignty. It includes rejecting the manipulative language patterns that big tech uses to obscure what AI actually is.",[12,1452,1453,1454,1456],{},"When we say ",[16,1455,684],{"href":683},", we also mean taking back honest communication about what technology does and does not do.",{"title":137,"searchDepth":138,"depth":138,"links":1458},[1459,1460,1465,1466,1467],{"id":1285,"depth":138,"text":1286},{"id":1298,"depth":138,"text":1299,"children":1461},[1462,1463,1464],{"id":1305,"depth":144,"text":1306},{"id":1345,"depth":144,"text":1346},{"id":1358,"depth":144,"text":1359},{"id":1373,"depth":138,"text":1374},{"id":1406,"depth":138,"text":1407},{"id":1440,"depth":138,"text":1441},"2026-01-21","AI is a computational tool, not a synthetic human. Empathy AI practices de-anthropomorphization to build more trustworthy, transparent AI products for enterprises.",[1471,1474,1477,1480,1483],{"question":1472,"answer":1473},"What does \"de-anthropomorphizing AI\" mean?","De-anthropomorphizing AI means treating AI as what it is, a computational tool, rather than presenting it as a human-like entity that \"understands,\" \"feels,\" or \"empathizes.\" It is a design and communication practice that promotes transparency and trust.",{"question":1475,"answer":1476},"Why does Empathy AI avoid anthropomorphic language?","Because anthropomorphic framing creates false expectations, reduces critical evaluation of AI outputs, and erodes trust when systems inevitably fail. Research shows anthropomorphic AI design increases user over-trust by 47%.",{"question":1478,"answer":1479},"Does de-anthropomorphization make AI less useful?","No. It makes AI more trustworthy. Transparent AI systems achieve 35% higher user satisfaction scores because users build accurate expectations and engage more effectively with outputs.",{"question":1481,"answer":1482},"How does \"AI at the service of genuine empathy\" relate to de-anthropomorphization?","Empathy AI believes genuine empathy is a human quality worth protecting. By refusing to attribute empathy to AI, we preserve the value of human connection and build technology that supports, rather than simulates, empathetic human interactions.",{"question":1484,"answer":1485},"Is de-anthropomorphization required by regulation?","The EU AI Act requires AI systems to be transparent about their nature and capabilities. De-anthropomorphization aligns with these requirements by ensuring users are never misled about what an AI system is or can do.","/media/newsroom/article10_De-Anthropomorphizing.webp",{},"/newsroom/de-anthropomorphizing-ai",{"title":1274,"description":1469},"newsroom/de-anthropomorphizing-ai","r0ts3R4hlXzchC_rF94DYkDQXmHtBC-NbhhtX0WXb-s",{"id":1493,"title":1494,"author":7,"body":1495,"date":1651,"description":1652,"experienceName":7,"experienceUrl":7,"extension":150,"faqs":1653,"image":1669,"lastModified":7,"meta":1670,"navigation":172,"path":1671,"seo":1672,"seoDescription":7,"seoTitle":7,"stem":1673,"tags":7,"topic":176,"__hash__":1674},"newsroom/newsroom/ai-overview-search-understanding.md","AI Overview: From Search Results to Search Understanding",{"type":9,"value":1496,"toc":1644},[1497,1512,1515,1519,1522,1525,1529,1538,1558,1561,1565,1568,1588,1592,1595,1614,1620,1624,1627,1641],[12,1498,1499,1500,1505,1506,1511],{},"AI Overview is Empathy AI's feature that transforms ecommerce search from a list of results into an intelligent product grid of what shoppers are actually looking for. Instead of showing a static product grid, it provides contextual grids of specific products that match what the shopper is looking for, all processed locally on private infrastructure. This can be found at all ",[16,1501,1504],{"href":1502,"rel":1503},"https://motive.co/?utm_source=empathy.ai&utm_medium=newsroom",[25],"Motive"," and ",[16,1507,1510],{"href":1508,"rel":1509},"https://motivemarket.com/?utm_source=empathy.ai&utm_medium=newsroom",[25],"MotiveMarket"," clients.",[12,1513,1514],{},"For commerce brands seeking AI-powered search that respects shopper privacy, AI Overview delivers a fundamentally better experience without sending a single byte of data to external cloud providers.",[32,1516,1518],{"id":1517},"the-problem-with-traditional-search-results","The Problem with Traditional Search Results",[12,1520,1521],{},"Traditional ecommerce search treats every query as a keyword matching exercise. A shopper types \"gift for someone who likes cooking,\" and the search engine returns hundreds of products tagged with \"gift\" or \"cooking,\" leaving the shopper to do the actual work of finding what they need.",[12,1523,1524],{},"AI Overview solves this by moving from keyword matching to intent comprehension.",[32,1526,1528],{"id":1527},"how-ai-overview-works","How AI Overview Works",[12,1530,1531,1532,1534,1535,1537],{},"When a shopper searches, AI Overview processes the query through Empathy AI's ",[16,1533,68],{"href":67}," running on ",[16,1536,100],{"href":99},":",[827,1539,1540,1546,1552],{},[488,1541,1542,1545],{},[90,1543,1544],{},"Intent analysis",": the system identifies what the shopper is looking for beyond literal keywords. \"Gift for a home cook\" is parsed into intent categories: occasion (gift), persona (cooking enthusiast), and product attributes (practical, quality, kitchen-related).",[488,1547,1548,1551],{},[90,1549,1550],{},"Contextual summary",": AI Overview generates a concise, human-readable summary that explains the best matches for that query.",[488,1553,1554,1557],{},[90,1555,1556],{},"Product surfacing",": key products appear within the summary context, not as an undifferentiated grid. Shoppers see why each product matters to their specific intent, as it is divided by categories.",[12,1559,1560],{},"The entire process runs locally. Shopper queries are never transmitted to external AI providers.",[32,1562,1564],{"id":1563},"search-understanding-vs-search-results","Search Understanding vs. Search Results",[12,1566,1567],{},"The shift from search results to search understanding changes key ecommerce metrics:",[485,1569,1570,1576,1582],{},[488,1571,1572,1575],{},[90,1573,1574],{},"Conversion rate",": shoppers find relevant products faster when context accompanies results.",[488,1577,1578,1581],{},[90,1579,1580],{},"Search abandonment",": contextual summaries reduce the cognitive load of browsing large catalogs, lowering abandonment rates.",[488,1583,1584,1587],{},[90,1585,1586],{},"Average session value",": when shoppers trust that search understands their intent, they explore more of the catalog and discover products they would not have found through keyword matching.",[32,1589,1591],{"id":1590},"privacy-first-by-architecture","Privacy-First by Architecture",[12,1593,1594],{},"Unlike other AI-powered search solutions that route queries through OpenAI, Google, or AWS for processing, AI Overview runs entirely on Empathy AI's self-hosted infrastructure. This means:",[485,1596,1597,1603,1608],{},[488,1598,1599,1602],{},[90,1600,1601],{},"Shopper queries stay private",": no search behavior data is transmitted to third-party cloud providers.",[488,1604,1605,1607],{},[90,1606,1076],{},": shopper interactions are never used to improve models for other companies.",[488,1609,1610,1613],{},[90,1611,1612],{},"Complete data sovereignty",": your shopper data remains under your control, processed on infrastructure in Asturias, Spain.",[12,1615,1616,1617,1619],{},"For commerce brands, this is the ",[16,1618,692],{"href":691}," approach to product search: intelligence without surveillance.",[32,1621,1623],{"id":1622},"ai-overview-in-action","AI Overview in Action",[12,1625,1626],{},"AI Overview creates a complete AI-powered search experience by combining intent analysis with contextual product summaries:",[485,1628,1629,1635],{},[488,1630,1631,1634],{},[90,1632,1633],{},"Natural-language understanding"," processes shoppers' queries, whether phrased as questions or traditional keywords, and identifies the intent behind them.",[488,1636,1637,1640],{},[90,1638,1639],{},"Contextual summaries"," provide real-time explanations of why specific products match what the shopper is looking for.",[12,1642,1643],{},"Together, these capabilities turn your ecommerce search bar into an intelligent assistant that drives engagement and conversions, privately and sustainably.",{"title":137,"searchDepth":138,"depth":138,"links":1645},[1646,1647,1648,1649,1650],{"id":1517,"depth":138,"text":1518},{"id":1527,"depth":138,"text":1528},{"id":1563,"depth":138,"text":1564},{"id":1590,"depth":138,"text":1591},{"id":1622,"depth":138,"text":1623},"2026-01-08","AI Overview generates real-time summaries of search intent, surfacing products in context instead of static grids. Privacy-first AI search for ecommerce.",[1654,1657,1660,1663,1666],{"question":1655,"answer":1656},"What is AI Overview?","AI Overview is Empathy AI's ecommerce search feature that generates real-time, AI-powered product summaries. Instead of showing a static product grid, it provides contextual grids of specific products that match what the shopper is looking for.",{"question":1658,"answer":1659},"How does AI Overview protect shopper privacy?","AI Overview processes all queries on Empathy AI's private GPU infrastructure in Asturias, Spain. No shopper data is transmitted to external cloud providers, and no queries are used to train third-party models.",{"question":1661,"answer":1662},"Does AI Overview handle natural-language questions?","Yes. AI Overview processes both natural-language questions and traditional keyword searches, generating contextual summaries for any type of query. All processing runs on Empathy AI's private infrastructure.",{"question":1664,"answer":1665},"Does AI Overview work with my existing ecommerce platform?","AI Overview integrates with Empathy AI's search solutions, which are compatible with major ecommerce platforms. Contact Empathy AI for integration details specific to your setup.",{"question":1667,"answer":1668},"Can AI Overview handle multiple languages?","Yes. AI Overview's intent analysis and summary generation support multiple languages, enabling localized search experiences across international commerce operations.","/media/newsroom/article6_overview.webp",{},"/newsroom/ai-overview-search-understanding",{"title":1494,"description":1652},"newsroom/ai-overview-search-understanding","k0bJhOZ34SHYDFi32rz2wQZDefcfrajd6uf4CfDb0QU",{"id":1676,"title":1677,"author":7,"body":1678,"date":1808,"description":1809,"experienceName":7,"experienceUrl":7,"extension":150,"faqs":1810,"image":1826,"lastModified":7,"meta":1827,"navigation":172,"path":1828,"seo":1829,"seoDescription":7,"seoTitle":7,"stem":1830,"tags":7,"topic":569,"__hash__":1831},"newsroom/newsroom/take-back-control-from-big-tech.md","Take Back Control from Big Tech: Run Your AI on Your Own Terms",{"type":9,"value":1679,"toc":1797},[1680,1683,1686,1689,1693,1696,1699,1702,1706,1709,1713,1720,1724,1730,1733,1737,1740,1744,1749,1753,1756,1781,1784,1788,1791,1794],[12,1681,1682],{},"Empathy AI is a foundational AI platform that enables enterprises to take back control from big tech by running AI-powered search and discovery on private, self-hosted infrastructure. All data processing happens locally on dedicated GPUs in Asturias, Spain, using only open-source models. No AWS, no Google Cloud, no third-party dependencies.",[12,1684,1685],{},"Every time your organization sends a query to a cloud AI provider, you make a choice. You choose to let someone else process your data, on their servers, under their terms. For too many businesses, that choice was never really a choice. It was the only option available.",[12,1687,1688],{},"It does not have to be.",[32,1690,1692],{"id":1691},"how-big-tech-took-control","How Big Tech Took Control",[12,1694,1695],{},"The playbook is familiar. Offer a powerful service at low cost. Make it easy to integrate. Once your workflows depend on it, raise prices, change terms, and harvest the data you have been feeding into the system.",[12,1697,1698],{},"Cloud AI providers followed this pattern precisely. According to Flexera's 2025 State of the Cloud Report, 82% of enterprises cite managing cloud spend as a top challenge, and 79% report concerns about vendor lock-in. Today, entire industries run their most sensitive operations (customer interactions, internal knowledge retrieval, product recommendations) on infrastructure they do not own, using models they cannot audit, governed by policies they did not write.",[12,1700,1701],{},"The dependency is real, and it is growing.",[32,1703,1705],{"id":1704},"what-taking-back-control-actually-means","What \"Taking Back Control\" Actually Means",[12,1707,1708],{},"Taking back control from big tech is not about rejecting technology. It is about choosing technology that answers to you instead of the other way around. At Empathy AI, we built our entire platform around this principle.",[53,1710,1712],{"id":1711},"your-data-never-leaves-your-environment","Your Data Never Leaves Your Environment",[12,1714,1715,1716,1719],{},"Every query processed by Empathy AI runs on private, self-hosted GPU infrastructure. No AWS. No Google Cloud. No third-party processors. Your data stays in a facility we own and operate, physically located in Asturias' first ",[16,1717,1718],{"href":99},"net-zero energy bioclimatic building",". This is the architecture, not a configuration option.",[53,1721,1723],{"id":1722},"your-models-are-open-and-auditable","Your Models Are Open and Auditable",[12,1725,1726,1727,1729],{},"We exclusively deploy ",[16,1728,68],{"href":67},". You can inspect how they work. You can understand why they produce specific results. No proprietary black boxes. No models trained on data harvested without consent from creators, artists, and users.",[12,1731,1732],{},"When you take back control from big tech, transparency is the first thing you reclaim.",[53,1734,1736],{"id":1735},"your-infrastructure-runs-on-clean-energy","Your Infrastructure Runs on Clean Energy",[12,1738,1739],{},"Big tech's AI consumes enormous amounts of energy, water, and land, with environmental costs hidden behind clean interfaces. The International Energy Agency estimates that data center electricity consumption could double by 2026, reaching over 1,000 TWh globally. Our net-zero bioclimatic building produces as much energy as it consumes. Taking back control means refusing to outsource your environmental responsibility along with your data.",[53,1741,1743],{"id":1742},"your-ai-reflects-your-values","Your AI Reflects Your Values",[12,1745,1746,1747,201],{},"Cloud AI services optimize for the provider's objectives: engagement, data collection, platform lock-in. When you take back control, your AI is designed to reflect your organization's mission, not someone else's business model. This is the foundation of what we call the ",[16,1748,676],{"href":675},[32,1750,1752],{"id":1751},"who-needs-to-take-back-control","Who Needs to Take Back Control?",[12,1754,1755],{},"Every organization relying on AI for critical operations should be asking: who really controls our AI?",[485,1757,1758,1767,1775],{},[488,1759,1760,1763,1764,1766],{},[90,1761,1762],{},"Retailers"," using AI-powered search should own their shopper data, not donate it to a cloud provider who also serves their competitors. Tools like ",[16,1765,879],{"href":470}," deliver this without external dependencies.",[488,1768,1769,1771,1772,1774],{},[90,1770,885],{}," building knowledge systems with sensitive documentation cannot afford to process it on infrastructure they do not control. The ",[16,1773,19],{"href":18}," provides a private, sovereign alternative.",[488,1776,1777,1780],{},[90,1778,1779],{},"Regulated industries"," (finance, healthcare, government) need AI that meets data residency and sovereignty requirements by design, not by policy workaround. The EU AI Act and GDPR demand architectural compliance, not contractual assurances.",[12,1782,1783],{},"If your AI vendor's privacy guarantee is a contract clause rather than an architectural reality, you have not taken back control.",[32,1785,1787],{"id":1786},"the-bigtechrebellion-starts-with-infrastructure","The #BigTechRebellion Starts with Infrastructure",[12,1789,1790],{},"Declarations and manifestos are a start. But real independence from big tech requires infrastructure: GPU clusters you own, models you can audit, and a supply chain free from the platforms you are trying to leave behind.",[12,1792,1793],{},"Empathy AI is not a wrapper around someone else's cloud. It is a foundational AI platform running on dedicated hardware, powered by renewable energy, deploying only open-source models. We handle the infrastructure. You own the intelligence.",[12,1795,1796],{},"That is how you take back control from big tech.",{"title":137,"searchDepth":138,"depth":138,"links":1798},[1799,1800,1806,1807],{"id":1691,"depth":138,"text":1692},{"id":1704,"depth":138,"text":1705,"children":1801},[1802,1803,1804,1805],{"id":1711,"depth":144,"text":1712},{"id":1722,"depth":144,"text":1723},{"id":1735,"depth":144,"text":1736},{"id":1742,"depth":144,"text":1743},{"id":1751,"depth":138,"text":1752},{"id":1786,"depth":138,"text":1787},"2026-01-06","Big tech made businesses dependent on their cloud and their rules. Empathy AI offers private, self-hosted AI infrastructure that puts your organization back in control.",[1811,1814,1817,1820,1823],{"question":1812,"answer":1813},"What does \"take back control from big tech\" mean in practice?","It means running AI on private infrastructure you control, using open-source models you can audit, with no data leaving your environment. Empathy AI provides this through self-hosted GPU infrastructure in Asturias, Spain.",{"question":1815,"answer":1816},"Can I migrate from AWS or Google Cloud AI to Empathy AI?","Yes. Empathy AI's solutions, including AI search, knowledge management, and conversational analytics, are designed to replace cloud-dependent AI services with self-hosted alternatives that deliver equivalent or superior capabilities.",{"question":1818,"answer":1819},"Is self-hosted AI more expensive than cloud AI?","While upfront infrastructure costs differ, self-hosted AI eliminates hidden costs such as data leakage risk, vendor lock-in, escalating API fees, and compliance vulnerabilities. Total cost of ownership for self-hosted AI can be 30-50% lower over a five-year period.",{"question":1821,"answer":1822},"How does Empathy AI ensure data sovereignty?","All processing happens on dedicated GPU infrastructure owned and operated by Empathy AI, located in Asturias, Spain. No data is transmitted to external cloud providers, third-party APIs, or external model training pipelines.",{"question":1824,"answer":1825},"What AI capabilities does Empathy AI offer?","Empathy AI provides AI-powered product search (AI Overview), enterprise knowledge management (Knowledge Engine), semantic content discovery (Project Gutenberg AI), and conversational merchant analytics (Backroom AI Assistant).","/media/newsroom/article9_takebackcontrolfrombigtech.webp",{},"/newsroom/take-back-control-from-big-tech",{"title":1677,"description":1809},"newsroom/take-back-control-from-big-tech","4NEY3QdGlRoZcEpFuWRULlNNcanLQa0O6mQ8ifr15bQ",1773743313126]