LangChain: evidence graphs boost agent accuracy 27% and cut cost 58%
LangChain · x · 2026-10-29
- LangChain's open-source wiki compiler OpenWiki serves as a persistent memory layer for agents: pre-compiling scattered policies, manuals, tickets and code so agents don't rebuild domain understanding each query.
- On complex cross-source questions, an agent using OpenWiki was 5x more accurate than grep-only retrieval.
- Adding a lightweight evidence graph (citations and document references turned into explicit graph edges) improved accuracy by 27%, doubled citation consistency, and cut cost per correct answer by 58% vs. wiki alone.
- Caveat: for simple lookups the memory-free agent was equally accurate and faster — the payoff is in repeated cross-source reasoning, e.g. banking/insurance policies that frequently amend each other.
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