Bounded consulting service
AI workflow reliability evaluation
You bring a sanitized workflow and a specific decision. I design controlled trials to investigate what selected models or agent workflows can do under the agreed conditions, where they fail, and what still requires human verification.
This is an evidence service, not a deployment guarantee. Findings apply to the recorded task, models, conditions, and trial count. They do not establish production safety or universal model rankings.
Questions an evaluation can investigate
- How do selected models or workflows perform on this defined task?
- What mistakes occur, and how consequential are they?
- Which outputs or decisions still require human checking?
- Do specified prompt, context, or input changes improve the observed results?
- What tradeoffs appear among accuracy, coverage, uncertainty, cost, and elapsed time?
- Can the evaluation become a repeatable benchmark for future trials?
How the engagement works
- Written scoping. We agree on the workflow, decision, evidence standard, deliverables, exclusions, communication channel, and response windows.
- Test design. I translate the requirements into representative tasks, acceptance checks, trial conditions, and a suitable machine, judgment, or hybrid oracle.
- Controlled trials. Selected models or workflows run under recorded conditions. Outputs, failures, usage, cost, and elapsed time are preserved where available.
- Verification. Results are checked against the agreed acceptance boundary, source records, executable checks, or documented expert criteria.
- Findings and handoff. You receive a written report and curated supporting test records. A reusable benchmark is a separately commissioned deliverable.
What you must supply
The starting point is a sanitized procedure or workflow with enough detail to make the work testable:
- What starts the workflow and what information is available.
- The required output, decision, or action.
- Applicable rules, exceptions, permissions, and escalation requirements.
- What makes a result acceptable, unacceptable, or uncertain.
- Representative fictional or sanitized examples, including difficult cases.
- A subject-matter expert when domain correctness is not fully captured in writing.
Do not send personal data or confidential information. If the important conditions cannot be represented safely, the question may need to be narrowed or the engagement may not be a suitable fit.
Written deliverables
The findings report documents:
- What was tested, including conditions and acceptance criteria.
- Observed performance by meaningful requirement or task category.
- Consequential failures and recurring patterns supported by the evidence.
- Outputs or decisions that still required human correction, escalation, or source checking.
- Recorded cost, usage, and elapsed-time information where available.
- Limitations, untested conditions, supported conclusions, and warranted next steps.
Service boundaries
I design evaluations, conduct controlled tests, and report evidence. The service does not include:
- Deploying a model or workflow into production.
- Integrating with your applications, accounts, data, or infrastructure.
- Operating the production process or making business decisions on your behalf.
- Ongoing monitoring, incident response, technical support, or model administration.
- Guaranteeing future model behavior, production performance, regulatory compliance, or business outcomes.
All project communication is written. This keeps requirements, questions, decisions, approvals, and scope changes documented.
Evidence of the method
The public portfolio contains five inspectable evaluation units covering broadcast-media conformance, controlled software-performance measurement, visual provenance, professional-report review, and agent engineering behavior.
View the public evaluation portfolio
Start with the question
Email a brief, non-confidential description of the workflow and the decision you need to make.