AI human QA

Human-in-the-loop QA for AI workflows

How to use real people as a lightweight QA layer around AI agents, automations, and generated outputs.

Request managed AI QA

What to ask a reviewer

  • Route low-risk work through automation
  • Send exceptions and sampled outputs to human reviewers
  • Require structured pass/fail/correction notes
  • Use small paid tasks before building complex internal ops
  • Track recurring failure patterns for prompt/workflow fixes

Good deliverable

A short report with pass/fail notes, specific issues, source links or screenshots, and a prioritized correction list. Keep the task bounded so approval is straightforward.

Suggested prompt for your job post

Please review this AI-generated output against the provided source material. Mark anything incorrect, unsupported, unclear, risky, or missing context. Return a concise issue list and recommended corrections.