For AI and platform teams

Govern AI execution without hardcoding every operational decision.

Configuration drift, hardcoded prompts and inconsistent model settings make promotion slow and production changes risky. Approved execution profiles replace them with governed, versioned configuration.

profile: onboarding.verify-identity v15prompt, model, tools, policies and memory scopeDraft

graph node: document-store.readbound as read-only MCP profileScoped

approval boundaryhuman review required for high-impact actionsRequired

Evaluation coverage0.92

Policy checks1.00

Manual approval points2

Configuration becomes inspectable before it becomes executable.

A graphical configuration workspace for composing prompts, model settings, tool bindings, policy checks, judge profiles and human approval boundaries before approval.

Profiles move through draft, evaluation and approval states.
Every promoted version carries its config hash and evaluation evidence.

Execution configuration

Everything an agent may do, as governed configuration

Execution behaviour is governed by versioned, approved profiles instead of application code — scoped by workflow, node and agent.

Which workflow an agent may execute
Which model and model configuration may be used
Which prompts and prompt versions are approved
Which tools and tool servers may be called
Which policies must be enforced
Which memory sources may be accessed
Which judges must evaluate the result
Which fallback or escalation path is permitted

Graphical Config Bench

Build and evaluate before production

Prompt development, workflow design and evaluation share one lifecycle — so what you test is what gets approved and enforced.

Prompt management

Version, compare and safely roll back approved prompts.

Offline evaluations

Score accuracy, groundedness, safety and policy compliance.

Synthetic testing

Generate edge cases, policy violations and tool failures.

Workflow building

Design routing, tools, policies, judges and approval stages.

Promotion and rollback

Release evidence travels with every change

Promotion is an approval, rollback is an approval — and both carry the evaluation evidence that justified them.

1. Design

Build prompts, workflows and policies in Graphical Config Bench.

2. Evaluate

Score accuracy, groundedness, safety and policy compliance.

3. Approve

Promote tested configuration through the approval lifecycle.

4. Release

Bindings distribute; release evidence travels with the change.

5. Roll back

Revert to a previous approved version — also an evidenced change.

Tested configuration promotes through approval instead of ad-hoc release steps.

When something goes wrong

Diagnose with the trace, fix with configuration

Governance traces show exactly which configuration executed, so fixing behaviour means changing an approved binding — not shipping a hotfix.

1. Detect

A failed run, drift signal or policy breach surfaces.

2. Inspect

Open the governance trace for the exact execution.

3. Compare

Approved versus executed: prompt, model, tools, policy.

4. Remediate

Change the approved binding — not the application code.

5. Validate

Re-run and confirm the corrected behaviour with evidence.

Every remediation links back to the workflow, decision and evidence that triggered it.

Framework independence

Independent of model, provider and framework

Governance should not lock in your stack. The SDK sits alongside your agent framework and governs configuration, not architecture.

Any model provider

Route across cloud, private and local models under one approval model.

Any agent framework

The in-process SDK wraps calls without changing business logic.

Any deployment

The same governed pattern runs in cloud, on-premises and edge.

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Connect one workflow

See approved execution profiles, in-process enforcement and local execution evidence for a single agent workflow.

Discuss one workflow