Expert network
Bring operating experience into how AI workers are built and tested.
Capture procedures, evidence requirements, exceptions and evaluation criteria with practitioners and customer subject-matter experts.
Operational knowledge
The difficult part of a procedure often lives outside the formal document.
Experienced practitioners know which evidence matters, where cases fail, when an exception is material and what a complete result looks like.
That knowledge can be captured with clear permissions and used to configure and evaluate a worker. Customer subject-matter experts remain central to organisation-specific procedures.
Review expert knowledge before it influences a worker.
The process records origin, review, permission and version state.
Stage 01
Qualify
Process continuity
The record moves forward to capture.
Contribution requires explicit permission, review and confidentiality boundaries.
Expert input supplements, not overrides, the customer’s approved procedures and accountable roles.
Worker responsibility
Turn practical judgement into reviewable operating artefacts.
Procedure sequences
Describe the real stages, handoffs and completion criteria.
Evidence requirements
Identify acceptable sources, gaps and signals of reliability.
Exceptions and escalation
Define edge cases, severity and when authorised review is required.
Evaluation cases
Create representative scenarios, rubrics and expected review outcomes.
Accountable role
Human judgement and approval
Evaluate the knowledge by how it improves worker behaviour.
- 01Cases contributed
- 02Exception coverage
- 03Review agreement
- 04Rubric completeness
- 05Corrections identified
- 06Approved versions
Work with experts
Define the practical knowledge your worker needs to capture and test.
We can discuss customer expert participation and, where available, relevant practitioner contribution.