Evidence copilot
Ask what works for a problem. The copilot answers strictly from Evidoria's evaluated practices and links every claim to its source — and tells you plainly when there's no matching evidence yet.
How does this work?
The copilot uses retrieval-augmented generation (RAG) — the same class of AI behind modern assistants, but anchored to a curated, expert-evaluated evidence base instead of the open web.
- Retrieve. Your question is matched against Evidoria's library of evaluated practices — by meaning, not just keywords — to find the most relevant evidence.
- Generate. A large language model (LLM) then writes an answer using only those retrieved practices, and links each claim back to its source.
- Stay honest. It never invents practices or numbers, and says so plainly when the evidence base doesn't yet cover your question.
This grounding is what makes the answers trustworthy and checkable. The system is designed, built and operated by C-NAPSE — the same applied-AI capability can be brought to other domains and evidence bases.