Use case
Post-Training Data From Domain Experts
Post-training data is expert-created material used after pretraining: supervised fine-tuning pairs, preference rankings, critiques, and RLHF support labels. The point is to teach or select a professional standard, not the average of the public web.
We are not a freelancer marketplace or traditional staffing company.
What is post-training data from domain experts
Post-training data is expert-created material used after pretraining: supervised fine-tuning pairs, preference rankings, critiques, and RLHF support labels. The point is to teach or select a professional standard, not the average of the public web.
The problem this use case solves
Web-scale text is mixed. For a vertical system, that mixture is the risk. Expert post-training data makes the target behavior inspectable. It does not, by itself, guarantee a leaderboard gain.
Work experts can run
- Expert-authored SFT pairs
- Preference and ranked comparisons
- Critiques used as training signal
- Policy-aligned refusals
- Adjudicated hard cases
Common mistakes
- Using the same items for SFT and later as an independent benchmark
- Preference without domain justification
- Unmaintained gold answers after a policy change
Need this capacity for a live program?
Share the profession, specialty, experience, location, headcount, hours, duration, and project description. We assemble the expert capacity.
- Need 25 licensed nurses for a clinical AI evaluation
- Need 15 attorneys in a specific practice area
- Need 20 PhD scientists for benchmark creation
- Need 30 senior software engineers for code evaluation