01
Model state
Separate conversation context, durable facts, workflow state, and external system truth.
All services
Delivered through Wolven Tech
Agentic AI Architecture with Durable State
Design tool-using AI systems with explicit state, durable memory, permission boundaries, evaluation, and recovery paths.
Target outcome
An agent architecture that can explain what happened, resume safely, and improve under evaluation instead of relying on prompt luck.
Good fit when
- Products moving from chat demos to multi-step workflows
- Agents that act across customer or tenant data
- Teams adding MCP tools or persistent memory
- Workflows that need approvals, replay, audit, or human handoff
What you receive
- Agent state and tool-boundary model
- Memory and provenance design
- Permission and approval policy
- Evaluation cases and failure taxonomy
- Reference implementation or architecture decision record
How the work runs
02
Constrain tools
Define scoped capabilities, validation, idempotency, and approval points.
03
Instrument
Record decisions and tool results so failures can be replayed and classified.
04
Evaluate
Use fixed tasks and outcome checks before expanding autonomy.