LangChain / LangGraph
Build and run stateful agent workflows with durable execution and explicit control flow.
Official product pageAvery Rulebook for LangChain and LangGraph
LangGraph provides durable orchestration, state and human-in-the-loop patterns. Rulebook supplies the governed enterprise decision that tells the graph whether to proceed, constrain or escalate.
The operating reality
The runtime compliance gate
Rulebook evaluates live context against the confirmed policy and regulatory rules that apply, then returns a decision the agent must follow.
Actor, purpose, data, jurisdiction and proposed action
Allow, deny, obligations or named human review
Evidence, rulebook version and signed decision trace
Architecture boundary
Build and run stateful agent workflows with durable execution and explicit control flow.
Official product pageCentralize confirmed policy logic and evidence behind a stable decision interface.
LangGraph owns workflow state and orchestration. Rulebook owns published enterprise rules and their decision record.
Why the gap persists
Policy logic becomes duplicated across nodes and agents.
Graph changes and policy approvals have different owners.
A workflow trace does not explain the authority behind a decision.
Rulebook in the workflow
Add a Rulebook node before a response, tool call or state transition.
Use structured allow, deny, obligations and review output to select the path.
Store the receipt with the graph run for end-to-end lineage.
Potential outcomes
Questions leaders ask
It can supply policy-driven conditions, but LangGraph remains responsible for workflow transitions and state.
Rulebook states when and which authority is required. LangGraph can pause and route the workflow to collect that approval.
Executive briefing
Bring one consequential agent workflow. We will map the governing policies and regulations, runtime gate, human authority and auditable evidence path with your team.
Request a briefing