Explore the 5 technical pillars to establish to transform your EDM into an interoperable RAG engine, without changing your business tools, leading to +30% relevance in your AI responses.
⚡ Why RAG isn't (yet) working in the enterprise
⚡ What needs to be prepared to achieve it
⚡ The 5 pillars to implement by 2026
Artificial intelligence is no longer a distant horizon. It's infiltrating everywhere, at all levels of the enterprise. Copilots, assistants, augmented search engines, document automation: use cases are multiplying. And yet, a majority of companies remain stuck at the POC stage.
Why? Because after the "wow" effect, reality sets in: AI invents nothing. It only exploits what it's given. However, in businesses, internal data is rarely ready. Too many silos. Too many versions. Too much noise. Not enough meaning.
What we quickly learn is that a good AI model isn't about marketing promises or a ChatGPT subscription. It's a matter of information engineering. It's the quality of the content, its structure, context, and governance, that makes all the difference.
In a world moving faster than our project cycles, we need to reverse the logic: curate your data before choosing your models. Test, yes. But test on a reliable foundation. Iterate, yes. But from understandable, up-to-date, filterable, shareable documents. In short, on a solid foundation.
This foundation is EDM. But not a static EDM, conceived as a digital filing cabinet. It's a transversal, modern, connected EDM that structures documents where they are produced. It organizes, cleans, and enriches them without overburdening your teams.
It will enable you to transform your documents into knowledge, and that knowledge into truly useful AI agents.
This white paper explains why — and especially how — to lay the technical foundations for your future enterprise AI, starting today.
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