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Knowledge mapped, not piled up
Line → Category → Product → Version → Feature: every document anchored to the right point. “Does product C support feature 3.2?” is answered by the map, not by a lucky search.
Engineering “cannibalizes” documentation time: 95% goes to new products, 5% to documenting. It is unavoidable — which is why the “R&D should document better” approach always fails. EKRAI solves the knowledge bottleneck another way: instant answers at the frontline, and for R&D only deep work, no phone calls.
The map organizes company intelligence around the logic of those who use information, not those who create it. Features, products, versions and documents linked on the Structured Knowledge Base — the Single Source of Truth — and queryable with maximum precision.
Line → Category → Product → Version → Feature: every document anchored to the right point. “Does product C support feature 3.2?” is answered by the map, not by a lucky search.
If an answer is incomplete or absent, an alert fires and becomes an asynchronous, tracked Knowledge Task with a change log. Bottom-up, not imposed from above: that is why it works where “document better” fails.
The “sieve” of Prompt Engineering and semantic structuring separates signal from noise: noise is dropped, knowledge stays structured and reusable. Even for complex analyses like bills of materials (BOM).
Variants, versions, compatibility, exceptions: the ground where generic prompts know nothing and RAG on raw documents confuses revisions and models. EKRAI's KAG works on knowledge already disambiguated by the map: maximum signal-to-noise, hallucinations trending to zero by progressive convergence. It is in knowledge-intensive processes like R&D that you reach a 70–90% productivity gain.
Weekly interruptions per person · response time to internal requests · reuse rate of existing solutions · Knowledge Tasks opened/closed · share of complete answers (growing) · time spent on innovation.
Let's build the map together: we start from your org chart, find the knowledge flows blocking R&D and estimate the recoverable productivity potential.