Expert network
Domain experts, in-house, on your project.
Good AI depends on people who know the subject. Our in-house expert network validates data, rates and ranks model outputs, and stress-tests systems before and after release.
What experts do
Four kinds of work.
Validate data and outputs
Check facts, logic and domain accuracy in datasets and in what models produce.
Rate, rank and compare
Give structured preference and quality judgments that guide model alignment.
Red team and stress-test
Probe systems for failures, bias and misuse, and document what they find.
Review physical-task data
Check that recordings of real tasks are correct, usable and within the brief.
How we work with experts
The standard we work to.
| Vetting | Experts are assessed on subject knowledge before joining a project. |
|---|---|
| Briefing | Each project starts with a written brief and worked examples so judgments are consistent. |
| Quality review | A second expert reviews a sample of the work on each project. |
| Fair terms | Experts work under written agreements. |
For experts
If you have deep knowledge in a field and want to apply it to AI, tell us about your background.
For teams
If your model needs specialist judgment, tell us the domain and the task.