GuideKnowledge management: why your initiatives fail, and what AI changes
Why knowledge management initiatives fail, what AI really changes about managing what a company knows, and what it will never change.
Turnkey enterprise RAG for every team
Every employee asks a question and finds useful information across your documents, tools, and knowledge bases. ATG connects your sources, secures access, and adapts the assistant to your business specifics.
By Jean-Christophe BudinUpdated on
Accurate answers, without the wait
We test ATG on FinanceBench, a public benchmark: 150 analyst questions over 368 filings of listed companies, all in one knowledge base, just like your internal documents. ATG posts the best score we have found, and answers in about ten seconds where the best published competitor takes over a minute.
See all our benchmarksFinanceBench
Correct answers
92%
Average time
11 s
Correct answers
86%
Average time
71 s
Ready-to-use connectors
Google Drive, SharePoint, Confluence, Notion, websites, files, FTP, business IT systems, SQL databases, and business sources: we connect your knowledge without starting from scratch.
Sovereignty and control
European-law hosting providers, controlled permissions, cited sources, and answer traceability so teams can trust the system.
Relevant to your business
Your vocabulary, processes, internal rules, and use cases are taken into account so answers are genuinely useful.
Go further
Selected articles and videos to better understand this solution and see how it works in practice.
Articles
Guide
GuideInternal company chatbot: how to scope the project right
Internal company chatbot: what it is really for, how it differs from a website chatbot, the classic pitfalls and the conditions for success.
GuideEnterprise RAG: 5 mistakes that show up after the POC
An enterprise RAG is relatively easy to prototype. Making it a useful, stable product is a much bigger challenge. Here are the five most common production pitfalls—and how to get ahead of them.
AIOn-premise LLM and RAG for the enterprise: what €60k really buys you
On-premise LLM in 2026: GPU prices, memory per model, full TCO and break-even against the same model via API. Figures to decide between Make and Buy.
12 min
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TutorialHow RAG Transforms Your AI into an Expert on Your Business
RAG and LLM: definition, how it works, choosing the model. The guide to connecting an LLM to your internal documents and enterprise data.
Digital SovereigntyWhat if the United States Turned Off Your Digital Tap?
How dependence on U.S. infrastructure exposes Europe to growing strategic risks - and what to do to protect yourself.
3 min
Frequently asked questions
What is enterprise RAG?
Enterprise RAG (Retrieval-Augmented Generation) connects an AI model to your internal documents and tools. Answers draw on your sources, with citations and access control, not only on a public chatbot’s generic training.
Why turnkey RAG instead of building in-house?
The expensive foundations (connectors, ingestion, retrieval, citations, permissions, evaluation, monitoring) already exist in ATG. You go to production faster, often with about 80% lower TCO than an internal build.
Who is an internal enterprise chatbot for?
For every employee who wastes time searching Drive, SharePoint, Confluence, Notion, or email. The internal chatbot answers from your knowledge, with inherited permissions and cited sources.
Do you offer on-premise / on-prem RAG?
Yes. On-premise / on-prem RAG does not always mean hosting the LLM yourself on GPUs: separate data and retrieval, the platform (connectors, permissions, citations), and inference. Depending on your constraints, ATG deploys with European hosting or on-premise: same data control and traceability, without rebuilding the full stack. For the cost of a fully local LLM, see: https://www.askthisguy.com/en/blog/llm-local-enterprise-sovereignty-illusion/
What does a sovereign chatbot mean in practice?
An assistant that answers from your sources, hosted under your control (Europe / on-prem), with citations and access rights. It is not a consumer chatbot trained on the open web.
Your knowledge, open to everyone
Show us your sources and constraints. We will quickly map how to deploy a sovereign, operational RAG assistant.