AI Reliability & Security Reviews
Review tool failures, permission boundaries, retries, observability and the risks around production workflows.
Discuss Your Project ↗Start with a concrete outcome.
This service is for founders and teams with a specific workflow, existing system or deployment challenge. We define success in terms of the work the system must perform, the constraints it must respect and the failures it must handle.
Where this service helps
A reliability review follows the path from untrusted input to tool execution and external effects. Inspect where instructions can cross trust boundaries, where retries can duplicate writes, and where failures can become invisible. Prioritize findings by the consequences of a failure and the evidence that the path is reachable.
Questions we resolve
- Where are permissions enforced outside the model?
- Which actions require approval and an audit trail?
- Can an operator stop, recover and reconcile the workflow?
Potential deliverables
A prioritized risk register, failure tests and a practical remediation plan. The final scope depends on your current systems and the evidence gathered during assessment.
How the engagement works
- Understand the workflow and review the current system.
- Identify the highest-risk assumptions and agree acceptance criteria.
- Validate with a bounded prototype or assessment.
- Implement, verify and document the agreed scope.
What to bring to the first discussion
A description of the current process, the tools involved, your data handling requirements, the intended users and your timeline. Avoid sending credentials or confidential documents through the inquiry form.
Scope and limitations
This is a scoped engineering review, not a certification or a promise that all vulnerabilities have been found.
Related engineering work
Understand the work before scoping it
Pick a problem you are working on. Each guide includes a method, sources and a tool or example to try.