# Harvey — Improving Agent Accuracy With Harvey Graph

- Company: Harvey (harvey.ai)
- Announced: 2026-10-19T16:00:00+00:00
- Category: capability-change
- Coverage: not counted
- Announcement: yes
- Group: announcements
- Source: https://www.harvey.ai/blog/improving-agent-accuracy-with-harvey-graph
- Record: https://forck.live/items/24654-improving-agent-accuracy-with-harvey-graph
- Subject: Harvey

Harvey is rolling out Harvey Graph, a context layer that maps how a firm's documents, matters, people and legal knowledge connect, so its agents start legal tasks already briefed instead of rebuilding context each time. The company says flat retrieval finds passages rather than relationships, forcing agents to re-discover the same entities and cross-references task after task and spend time and tokens recovering structure already in the documents. Harvey Graph today combines a knowledge graph covering US Case Law and a per-Space context graph of matters, data and documents from Vaults and integrations, and it follows each Space's governance and security settings without user management. Harvey says users will not have to know the graph is there or activate it, but will notice the agent asking less up front while returning work verifiable with citations. The company says the investment is far from complete and plans precedent flags, cite checking, law evolution tracking, a new legal research surface and firm-defined legal ontologies in coming months. Harvey also says graph value compounds with its memory work, which will accrue to Spaces and stay transparent, traceable and under the user's control.

## Evidence

Verbatim from https://www.harvey.ai/blog/improving-agent-accuracy-with-harvey-graph:

> Flat retrieval (chunks ranked by similarity) finds passages, not relationships. An agent working this way re-discovers the same entities and cross-references task after task, spending time and tokens to recover structure that was already in the documents.

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