{"id":16270,"date":"2026-10-15T10:26:52","date_gmt":"2026-10-15T08:26:52","guid":{"rendered":"https:\/\/yeeply.com\/en\/blog\/what-is-rag-ai-company-data\/"},"modified":"2026-10-15T10:26:56","modified_gmt":"2026-10-15T08:26:56","slug":"what-is-rag-ai-company-data","status":"publish","type":"post","link":"https:\/\/yeeply.com\/en\/blog\/what-is-rag-ai-company-data\/","title":{"rendered":"What Is RAG? How to Build an AI That Answers From Your Company&#8217;s Data"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"16270\" class=\"elementor elementor-16270 elementor-bc-flex-widget\" data-elementor-post-type=\"post\">\n\t\t\t\t\t\t<section class=\"elementor-section elementor-top-section elementor-element elementor-element-r4g9a01 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"r4g9a01\" data-element_type=\"section\" data-e-type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-r4g9a02\" data-id=\"r4g9a02\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-r4g9a03 elementor-widget elementor-widget-html\" data-id=\"r4g9a03\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"html.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<p>Ask ChatGPT about your holiday policy, your price list or the terms of a contract you signed last spring and it will either admit it doesn't know or, worse, give you a confident answer that's wrong. It has never seen your documents. <strong>RAG<\/strong> is the technique that fixes this, and it's behind most of the \"ask our documentation\" assistants companies have launched over the last two years.<\/p>\n<p>So, what is RAG? It's a way of connecting an AI model to your own information so it answers from your manuals, policies, contracts and knowledge base instead of from memory. This guide explains how it works in plain English, where it gets its information, how it handles permissions and security, what it costs to build and where it pays off. If you already know you want one, you can skip to the <a href=\"#rag-cost\">cost section<\/a> and work out an estimate for your case.<\/p>\n<details style=\"margin-bottom:1.5em;padding:1em;background:#f5f5f5;border-radius:6px\"><summary style=\"cursor:pointer;font-weight:600\">Contents<\/summary>\n<ul style=\"margin-top:.8em\">\n<li><a href=\"#what-is-rag\">What is RAG?<\/a><\/li>\n<li><a href=\"#rag-vs-chatgpt\">RAG vs ChatGPT: what's the difference?<\/a><\/li>\n<li><a href=\"#where-rag-gets-information\">Where does a RAG system get its information?<\/a><\/li>\n<li><a href=\"#permissions\">Permissions: who can see what<\/a><\/li>\n<li><a href=\"#keeping-up-to-date\">Keeping the information up to date<\/a><\/li>\n<li><a href=\"#citing-sources\">Citing sources: why it matters more than it seems<\/a><\/li>\n<li><a href=\"#security\">Security and privacy<\/a><\/li>\n<li><a href=\"#rag-cost\">How much does it cost to build a RAG system?<\/a><\/li>\n<li><a href=\"#use-cases\">RAG use cases that pay off<\/a><\/li>\n<li><a href=\"#how-to-start\">How to start a RAG project<\/a><\/li>\n<\/ul><\/details>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-r4g9a04 elementor-widget elementor-widget-text-editor\" data-id=\"r4g9a04\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<h2 class=\"wp-block-heading\" id=\"what-is-rag\">What is RAG?<\/h2>\n<p>RAG stands for <strong>retrieval-augmented generation<\/strong>. The name comes from a <a href=\"https:\/\/arxiv.org\/abs\/2005.11401\" target=\"_blank\" rel=\"noopener noreferrer\">2020 research paper by Lewis and colleagues at Facebook AI Research<\/a>, and it describes the two steps the system takes every time someone asks a question:<\/p>\n<ol class=\"wp-block-list\"><li><strong>Retrieval.<\/strong> The system searches your documents and picks out the handful of passages most likely to contain the answer.<\/li><li><strong>Generation.<\/strong> It sends those passages to a language model (GPT, Claude, Gemini, Llama or similar) together with the question and an instruction: answer using only this text, and say so if the answer isn&#8217;t there.<\/li><\/ol>\n<p>The model still writes the answer, so it reads naturally. But the facts come from your documents, not from whatever the model absorbed during training. That&#8217;s the whole idea.<\/p>\n<p>To make the search work, the documents are prepared in advance. Their text is extracted, split into short passages and stored in an index that can be searched by meaning rather than exact words. That&#8217;s why someone can ask &#8220;how many days off do I get after my first year?&#8221; and find the paragraph headed &#8220;Annual leave entitlement&#8221;.<\/p>\n\n<h2 class=\"wp-block-heading\" id=\"rag-vs-chatgpt\">RAG vs ChatGPT: what&#8217;s the difference?<\/h2>\n<p>ChatGPT, Copilot or Gemini used on their own are general assistants. They&#8217;re very good at writing, summarising and reasoning, and they know a great deal about the world up to their training date. What they don&#8217;t know is anything specific to your company, unless someone pastes it into the conversation.<\/p>\n<p>A RAG system does that pasting automatically, for every question, with the right documents, and only the ones the person asking is allowed to see.<\/p>\n<figure class=\"wp-block-table\"><table><thead><tr><th><\/th><th>General chatbot (ChatGPT as is)<\/th><th>RAG system<\/th><\/tr><\/thead><tbody><tr><td>Where answers come from<\/td><td>What the model learned in training<\/td><td>Your own documents, searched at the moment of each question<\/td><\/tr><tr><td>Company-specific information<\/td><td>Only if you paste it in<\/td><td>Built in, from all the connected sources<\/td><\/tr><tr><td>When a document changes<\/td><td>Doesn&#8217;t find out<\/td><td>Uses the new version from the next re-index<\/td><\/tr><tr><td>Shows its source<\/td><td>No<\/td><td>Yes, document and page<\/td><\/tr><tr><td>When it doesn&#8217;t know<\/td><td>May invent a plausible answer<\/td><td>Can be told to say &#8220;I can&#8217;t find that&#8221;<\/td><\/tr><tr><td>Permissions<\/td><td>Not applicable<\/td><td>Each user only gets answers from what they can access<\/td><\/tr><\/tbody><\/table><\/figure>\n<p>People often ask whether they should &#8220;train ChatGPT on their data&#8221; instead. That&#8217;s called fine-tuning, and for company knowledge it&#8217;s usually the wrong tool. It&#8217;s expensive, has to be repeated whenever the information changes and still can&#8217;t tell you where an answer came from. Fine-tuning is useful for teaching a model a style or a format. RAG is what you want for facts.<\/p>\n\n<h2 class=\"wp-block-heading\" id=\"where-rag-gets-information\">Where does a RAG system get its information?<\/h2>\n<p>From wherever your documents already live. A well-built system reads from the existing sources rather than asking everyone to move files to a new tool. The usual ones are:<\/p>\n<ul class=\"wp-block-list\"><li>SharePoint, OneDrive and Google Drive folders<\/li><li>Wikis and knowledge bases such as Confluence or Notion<\/li><li>Document management systems, where contracts and case files tend to sit<\/li><li>Help-desk articles and past support tickets<\/li><li>Structured data from a CRM, ERP or internal database, when answers depend on live figures<\/li><\/ul>\n<h3 class=\"wp-block-heading\" id=\"what-documents-work-best\">Which documents work best<\/h3>\n<p>Clean digital text (Word files, Google Docs, PDFs exported from a computer) is the easy case. Things get harder, and more expensive, with scanned or photographed pages, complex tables and spreadsheets, technical drawings and anything still on paper. All of that has to be turned into readable text before the AI can use it, and it&#8217;s the part of the budget companies underestimate most often.<\/p>\n<p>The other trap is quality. If your shared drive holds three versions of the same policy, the system will find all three. Part of any serious project is deciding which documents are the source of truth and leaving the rest out.<\/p>\n\n<h2 class=\"wp-block-heading\" id=\"permissions\">Permissions: who can see what<\/h2>\n<p>This is the question that turns a two-month project into a five-month one, and the one almost nobody raises in the first meeting.<\/p>\n<p>If everyone in the company can open every document, permissions are simple. In most companies they can&#8217;t: HR files, board minutes, salary bands and client contracts are restricted. A RAG system must respect those restrictions in every answer. Otherwise anyone could ask the assistant what they couldn&#8217;t open directly, and the AI would happily summarise it for them.<\/p>\n<p>There are three common levels:<\/p>\n<ul class=\"wp-block-list\"><li><strong>Open to all.<\/strong> One shared knowledge base, no restrictions. The cheapest option and fine for public-facing help content.<\/li><li><strong>By department.<\/strong> Sales sees sales material, engineering sees technical docs. Moderate effort.<\/li><li><strong>Per person or per client.<\/strong> The system checks the original permissions of each document for each user, usually by reading them from SharePoint or Google Drive. The most robust option and the most work.<\/li><\/ul>\n\n<h2 class=\"wp-block-heading\" id=\"keeping-up-to-date\">Keeping the information up to date<\/h2>\n<p>One of the main advantages of RAG over a retrained model is that updates are cheap. When a document changes, only that document needs to be read and indexed again. How often that happens is a design decision:<\/p>\n<ul class=\"wp-block-list\"><li>A nightly or weekly sync is enough when documents rarely change.<\/li><li>Near-real-time updates make sense for support content, price lists or anything that changes several times a week.<\/li><li>Deleted or expired documents must also disappear from the index, which is easy to forget and causes some of the most embarrassing wrong answers.<\/li><\/ul>\n\n<h2 class=\"wp-block-heading\" id=\"citing-sources\">Citing sources: why it matters more than it seems<\/h2>\n<p>A RAG system knows exactly which passages it used for each answer, so it can show them. Some projects stop at naming the document. Others link to the exact page and let the user open it in one click.<\/p>\n<p>This sounds like a nice extra. In practice it&#8217;s what decides whether people trust the tool. An employee who can check the source in two seconds will rely on the answer; one who can&#8217;t will go back to asking a colleague. Citations also make mistakes visible quickly, which is how the system gets better.<\/p>\n\n<h2 class=\"wp-block-heading\" id=\"security\">Security and privacy<\/h2>\n<p>The first question most IT and legal teams ask is whether company documents will end up training someone else&#8217;s AI. With business contracts from the main providers, they won&#8217;t. OpenAI, for example, states that it <a href=\"https:\/\/openai.com\/enterprise-privacy\/\" target=\"_blank\" rel=\"noopener noreferrer\">does not train its models on business data<\/a> sent through its API or enterprise products, and Microsoft documents how to <a href=\"https:\/\/learn.microsoft.com\/en-us\/azure\/search\/retrieval-augmented-generation-overview\" target=\"_blank\" rel=\"noopener noreferrer\">build RAG with Azure AI Search inside your own Azure environment<\/a>.<\/p>\n<p>Beyond that, the decisions that matter are:<\/p>\n<ul class=\"wp-block-list\"><li><strong>Where the data is processed.<\/strong> For European companies, using EU data centres is normally a requirement under GDPR.<\/li><li><strong>Which model.<\/strong> For especially sensitive information (health, finance, legal) the system can run on open models deployed in your own cloud, so nothing leaves your infrastructure.<\/li><li><strong>Logging.<\/strong> Who asked what, and which documents were used, should be recorded and reviewable.<\/li><li><strong>Transparency.<\/strong> If customers or the public use the assistant, the <a href=\"https:\/\/eur-lex.europa.eu\/legal-content\/EN\/TXT\/?uri=CELEX:32024R1689\" target=\"_blank\" rel=\"noopener noreferrer\">EU AI Act<\/a> requires telling them they are talking to an AI.<\/li><\/ul>\n\n<h2 class=\"wp-block-heading\" id=\"rag-cost\">How much does it cost to build a RAG system?<\/h2>\n<p>Less than most people expect for a pilot, and more than they expect for a company-wide system. The AI model is rarely the expensive part. The price is driven by the number and state of the documents, how many places they live in, the permission model and whether answers must cite page-level sources.<\/p>\n<figure class=\"wp-block-table\"><table><thead><tr><th>Type of project<\/th><th>Typical scope<\/th><th>Build cost<\/th><th>Running costs<\/th><\/tr><\/thead><tbody><tr><td>Pilot<\/td><td>One team, one source, clean documents, simple web interface<\/td><td>\u20ac5,000\u201315,000<\/td><td>\u20ac150\u2013600\/month<\/td><\/tr><tr><td>Departmental<\/td><td>Several sources, department permissions, citations, Teams or Slack<\/td><td>\u20ac15,000\u201335,000<\/td><td>\u20ac600\u20132,000\/month<\/td><\/tr><tr><td>Company-wide<\/td><td>Many sources, scanned documents, per-user permissions, sensitive data<\/td><td>\u20ac35,000\u201360,000+<\/td><td>from \u20ac2,000\/month<\/td><\/tr><\/tbody><\/table><\/figure>\n<p>These are indicative ranges for the European market, excluding VAT. Running costs cover the AI model, the search index and hosting, and they grow with the number of questions asked, so a tool used by 20 people costs far less to run than one open to all your customers.<\/p>\n<p>Where the team is based also moves the number. Many of the certified companies in Yeeply&#8217;s network are in Spain, where senior AI engineering costs well below London or New York rates for the same level of experience. On a project of this size that difference is often what makes the business case work.<\/p>\n<p>For a figure closer to your own case, our calculator asks ten questions about your documents, where they&#8217;re stored and who needs access:<\/p>\n<iframe src=\"https:\/\/calculadora.yeeply.com\/c\/how-much-does-a-rag-system-cost-ai-that--8bd39c\" title=\"Calculator: how much does a RAG system cost\" loading=\"lazy\" style=\"width:100%;height:900px;border:0;border-radius:16px;\" allow=\"clipboard-write\"><\/iframe>\n\n<h2 class=\"wp-block-heading\" id=\"use-cases\">RAG use cases that pay off<\/h2>\n<p>Employees spend a large share of their week looking for information. A widely cited <a href=\"https:\/\/www.mckinsey.com\/industries\/technology-media-and-telecommunications\/our-insights\/the-social-economy\" target=\"_blank\" rel=\"noopener noreferrer\">McKinsey study<\/a> put it at 1.8 hours a day for office workers whose job is mostly handling information. These are the cases where a RAG system recovers that time fastest:<\/p>\n<h3 class=\"wp-block-heading\" id=\"internal-knowledge\">Internal knowledge and onboarding<\/h3>\n<p>HR policies, procedures, product information and &#8220;how do we do this here&#8221; questions. New hires stop interrupting the same three people, and those three get their afternoons back.<\/p>\n<h3 class=\"wp-block-heading\" id=\"customer-support\">Customer support<\/h3>\n<p>Either customer-facing, answering from your help centre and passing anything unclear to a person, or agent-facing, showing support staff the right paragraph of the manual next to each ticket. The second is a safer place to start.<\/p>\n<h3 class=\"wp-block-heading\" id=\"legal-compliance\">Legal, compliance and contracts<\/h3>\n<p>Finding a clause, a renewal date or an obligation across hundreds of contracts, regulations or case files, with a link to the exact page. Citations and permissions matter most here.<\/p>\n<h3 class=\"wp-block-heading\" id=\"sales-proposals\">Sales proposals and tenders<\/h3>\n<p>Drafting answers to RFPs from past proposals, case studies and technical sheets. The first draft takes minutes instead of days, and the bid team spends its time on what&#8217;s new.<\/p>\n<h3 class=\"wp-block-heading\" id=\"field-technical\">Field engineers and technical documentation<\/h3>\n<p>Technicians ask about a machine or installation from their phone and get the answer from the manual, including scanned sheets and drawings.<\/p>\n<p>If the assistant also needs to <em>do<\/em> things, such as updating a CRM record or booking a visit, it goes beyond RAG and becomes an <a href=\"https:\/\/yeeply.com\/en\/ai-agent-development\/\" target=\"_blank\" rel=\"noopener noreferrer\">AI agent<\/a>. And if what you need is a chatbot that reads live data from your CRM or ERP rather than documents, we explain the difference in <a href=\"https:\/\/yeeply.com\/en\/blog\/whats-the-difference-between-a-basic-chatbot-and-one-connected-to-your-data\/\" target=\"_blank\" rel=\"noopener noreferrer\">basic chatbots vs chatbots connected to your data<\/a>.<\/p>\n\n<h2 class=\"wp-block-heading\" id=\"how-to-start\">How to start a RAG project<\/h2>\n<p>The projects that work start small and measured:<\/p>\n<ol class=\"wp-block-list\"><li><strong>Pick one team and one question type.<\/strong> &#8220;Support agents answering product questions&#8221; is a good scope. &#8220;All company knowledge&#8221; is not.<\/li><li><strong>Gather 50 to 100 real questions<\/strong> that team asks, with the correct answers. This becomes the test that tells you whether the system works.<\/li><li><strong>Audit the documents<\/strong> behind those answers: where they are, what format, how current, who can see them.<\/li><li><strong>Build the pilot and measure it<\/strong> against the question set before anyone relies on it.<\/li><li><strong>Widen gradually<\/strong> to more sources and teams once accuracy is where it needs to be.<\/li><\/ol>\n<p>At Yeeply we help with exactly this. We work out the scope with you, bring you proposals from certified companies in our network that have built similar systems, and oversee the build through to launch. You can see what that involves on our <a href=\"https:\/\/yeeply.com\/en\/rag-development-services\/\" target=\"_blank\" rel=\"noopener noreferrer\">RAG development services<\/a> page.<\/p>\n<p>If you&#8217;d like a proposal for your case, click <strong>&#8220;Receive price estimate&#8221;<\/strong> at the top right of this page or write to sales@yeeply.com. Tell us what documents you have, where they live and who needs answers from them.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>What is RAG? A plain-English guide to AI that answers from your company&#8217;s documents: how it works, permissions, security, costs and use cases. Prices included.<\/p>\n","protected":false},"author":32,"featured_media":16266,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"_uag_custom_page_level_css":"","footnotes":""},"categories":[631,291],"tags":[],"class_list":["post-16270","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-how-much-does-it-cost-ai","category-blog"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.2 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>What Is RAG? AI That Answers From Your Company Data<\/title>\n<meta name=\"description\" content=\"What is RAG? A plain-English guide to AI that answers from your company&#039;s documents: how it works, permissions, security, costs and use cases. 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