When an AI agent makes the business decision
Some agents do more than orchestrate workflows or call predefined business functions. They investigate a case, gather evidence, consult business rules, and decide what the organization should do.
A claims agent may decide whether to approve a claim. A support agent may determine what compensation a customer is entitled to. A financial-services agent may decide whether a request can proceed autonomously or requires human approval.
In these systems, the LLM can investigate and gather context. The organization may not want the model itself to be the final authority on policy.
Knowledge separates the two.
AI investigates. Knowledge makes the policy determination.
Why a policy decision is not the same as enforcement
Knowledge tells the agent what the policy says. But if the agent is responsible for respecting that decision, the control remains advisory.
Consider a governed refund flow. Knowledge evaluates the case and returns ALLOWED for a small refund on TX-456, or BLOCKED for a larger one on TX-999. The agent, holding the decision, could still ignore or diverge from it :
Knowledge : refund TX-456 €40 -> ALLOWED
Agent : refund TX-456 €4,000
Knowledge : refund TX-999 -> BLOCKED
Agent : calls refund API anyway
An advisory verdict is documentation. Enforcement makes the tool boundary itself refuse actions that were not authorized by the exact operation Knowledge saw.
What Enforcement changes
Turn the policy determination into authorization the execution boundary can verify.
Every response from /check and /resolve carries a signed authorization envelope (JWS ES256). A downstream Policy Enforcement Point verifies the signature and the exact operation bindings (action, actor, resource, parameters) before running the underlying business API.
An agent's intent is not authority. Governed actions require proof of policy authorization.
How signed authorization works
Every decision carries three sections plus timing metadata :
signed_verdict:
authorization:
action: refund_execute
actor: principal:agent:support-agent-17
on_behalf_of: principal:human:marie@bank.com
on_behalf_of_authenticated: true
resource: TX-456
parameters:
amount_eur: 40
decision:
outcome: allowed
dominating_rule_id: rul-refund-under-100
cited_rule_version_ids: [rv-r1, rv-r2, rv-r7]
normative_hash: sha256:9f2a...
context_hash: sha256:f4c1...
issued_at: 1787500000
expires_at: 1787500060
Signature : ECDSA P-256. Verifiable offline against a per-tenant JWKS document. Full concept walkthrough at Signed verdicts and PEP ; source spec at docs/specs/signed-verdict-v1.md in the monorepo.
The four-actor trust chain
Human Principal -> Agent Principal -> Knowledge -> PEP -> Business API
(Marie) (support-agent-17) (PDP) (wrapper) (refund_api)
- Human Principal : authenticated at UI/SSO. Owns the delegation act.
- Agent Principal : authenticated at the API layer. Its API key binds to a
principal_idin Knowledge. - Knowledge : renders the decision and signs the envelope.
- PEP : the wrapper that verifies signature + bindings, runs the underlying API on success.
- Business API : trusts only the PEP.
Knowledge tightens two edges of this chain : Knowledge to PEP (the signature) and agent to PEP (the binding check). The other edges depend on your architecture. The signed verdict makes explicit which claims Knowledge authenticates and which the PEP must not blindly trust.
Three adoption paths
| Path | Fit | Client effort |
|---|---|---|
| MCP proxy | Agent stacks running MCP (Claude Desktop, Cursor, IDE plugins with an MCP server) | Insert the proxy in front of your MCP server. Zero code change on your tools. |
| Python SDK decorator | Python backends exposing tools to agents | Install knowledge-runtime, add @governed_tool(action, resource, bind) per tool. |
| Custom PEP | Any language, any framework, at your business API boundary | Verify the JWS envelope against Knowledge JWKS and compare bindings before executing. Small library, no framework dependency. |
The MCP proxy is the smoothest path for teams already running MCP. Ships as a drop-in that reads a registry file declaring which tools are governed. Your MCP server, your tool implementations, your host client all stay unchanged.
What Knowledge does not promise
Being explicit here is part of the enforcement contract, not a caveat.
- Every path to a business API goes through a PEP : your network and IAM policies must prevent agents from reaching un-wrapped APIs directly. If the agent can bypass the wrapper, the signed verdict provides no enforcement.
- The delegating human is trustworthy : the
on_behalf_ofclaim is authenticated only when a delegation token or an identity binding backs it. Otherwise the PEP must treat it as untrusted metadata. - Caller-asserted facts are truthful : facts fed into
/resolveare hashed for audit but not authenticated per field. Fact provenance is orthogonal. - A signed verdict cannot be replayed : replay protection is a PEP-side spent-verdicts store. Enable for operations that must execute exactly once.
- A signed verdict survives arbitrary delays : verdicts carry an expiry (default 60 seconds, configurable). Long-running flows re-consult after human approval.
What this changes for you
- Provable authorization trace. Every wrapped execution has a cryptographic artifact citing the exact rules that authorized it, at a specific policy state, for a specific agent principal, on a specific resource with specific parameters. Audit reconstruction is deterministic.
- Sub-forgery hardened. An agent cannot forge its principal by putting a different value in a JSON body. The
actorclaim is derived from Knowledge's authentication of the caller, not from the request payload. - Tampered-in-transit detection. Any modification of the signed envelope invalidates the signature.
- Grant-vs-execution binding. A signed verdict authorizing one operation cannot be reused for another. The binding is embedded in the signature.
Status - shipped 2026-08
M1 through M4bis complete. 121 tests. CI green. Available today in design-partner deployments ; production certification (SOC 2, ISO 27001) starts with the design-partner cohort.
Quickstart 5 min · MCP proxy setup · Talk to us
Related
| Read next | Why |
|---|---|
| Product | The decision loop for rule-governed AI agents |
| Auditability | The audit surface the signed envelope powers |
| Integrations | MCP + Python SDK + JWKS spec |
| Security | Trust model, keys inventory, rotation policy |
