Eligibility rule
- owner
- Policy owner
- version
- v3
- in force
- 2026-03-01
AI agents fail when the knowledge around them is stale, contradictory, or impossible to execute consistently. WiseWare turns policies, decisions, and cases into governed memory: source-backed records and executable rules that form a deterministic procedural substrate.
A document can say what should happen. It cannot reliably decide which version applies, which policy still holds, or what evidence a case must have before a decision is allowed. Without deterministic procedures, every agent run becomes a fresh interpretation of stale material.
Nobody knows which policy version to apply.
A case needs one current version, an owner, and a review state before anyone can apply it.
A case was decided on a policy that had since changed.
Cases need to cite the version in force, or decisions quietly drift away from the approved rule.
A case was approved without the required evidence.
Decisions should check that every criterion has its supporting evidence before the case is closed.
The same facts produce different outcomes.
When facts, rules, and decisions drift apart, each caseworker reinterprets the policy from scratch.
The missing layer is operational memory: rules that stay current, cite their evidence, and run the same way every time.
Underneath the workspace is a governed knowledge layer: records, rules, evidence, ownership, and review state. It gives agents the context they need to act, and gives people a way to inspect, approve, and correct what the agent is using.
WiseWare never lets AI silently rewrite your company's memory. It proposes changes from real sources, keeps a human in the loop, and turns approved decisions into knowledge you can stand behind.
An intake form, policy, case note, decision, or evidence file enters WiseWare without replacing the system where work happened.
WiseWare extracts the durable parts: decisions, obligations, evidence, owners, state, and citations.
A reviewer approves, edits, or rejects the change with the source beside it before anything becomes canonical memory.
Approved records become versioned memory that can be checked, linked, exported, and cited by people or AI.
It stores the records an agent can actually use: rules, decisions, evidence, owners, permissions, state, and history. When the agent asks, memory returns the right context with the procedure and proof attached.
Applying policy to real cases is the clearest entry point. Evidence has to survive, decisions have to be traceable, and answers have to be defensible. The same foundation works for customer promises, product decisions, and operations.
See domain examplesEvery useful AI workflow needs knowledge it can actually trust. That matters most when decisions carry legal, financial, or safety weight. And the foundation has to outlast whichever model you run today.