Colibri Coworker

solutions

Agentic AI governance

Governing an AI agent is not a matter of restricting its wording. It requires a control plane that decides what the agent may do, forces evidence before work counts as done, and keeps a record no participant can rewrite. Colibri Coworker applies those controls to every objective it accepts.

The governance controls

Verification before completion

Every mutation is checked against an expected postcondition. A model asserting success is never accepted as evidence, so a completed task carries an observation that can be re-read later.

Human approval checkpoints

Approval policies stop the agent before irreversible actions: external communication, deletion, spend, publishing and permission changes. Each request states the reason, affected system, input data, expected result, risk level and reversibility.

Append-only audit trail

Task transitions, tool calls, observations, verifications and approval decisions are recorded in an immutable log. Records cannot be edited or deleted, so any completion claim can be audited after the fact.

Bounded autonomy

Five autonomy levels, retry budgets, replan limits, circuit breakers and cancellation keep an agent inside an agreed operating envelope instead of relying on prompt instructions alone.

Typed tool registry

Agents act only through declared tools with typed inputs. Capability is granted explicitly rather than inferred from free-form model output.

Data residency on your engine

Reasoning runs on your own Colibri inference engine over its OpenAI-compatible API, reached through a public secured endpoint, a private network or a local companion gateway.

The lifecycle an auditor can follow

  1. 1. Objective is recorded with its context and priority.
  2. 2. Plan is validated against a schema: ordered steps, tools, postconditions, retry policy, dependencies and approval points.
  3. 3. Steps execute one bounded action at a time through the typed tool registry.
  4. 4. Observations are captured from the affected system, not from the model's narration.
  5. 5. Verification compares each observation with the declared postcondition.
  6. 6. Approval checkpoints pause the task where policy requires a human decision.
  7. 7. Completion is recorded only once verification passes, and every real action is metered as a Coworker Action.

Questions reviewers ask

How do we know the agent actually did the work?
Each action produces an observation that is verified against the postcondition declared in the plan. Unverified steps do not advance the task to completed.
Where does a human stay in the loop?
At approval checkpoints defined by policy, not at the model's discretion. Pending decisions queue on the Approvals screen with full context before anything runs.
What is the record of an incident?
The activity log holds the ordered trail of state transitions, tool calls, observations, verifications and decisions for every task, with each billable Coworker Action attributable to a specific tool call.
How is simulated work distinguished from real work?
Demo mode is labelled as simulated everywhere it appears and is never metered as a real Coworker Action.