Experts
Where your professional judgment shapes frontier AI
Why Human Edge
Built for professionals
who care about rigor
We built Human Edge for practitioners who find generic labeling work beneath their expertise. This is structured, methodologically serious work (evaluation, data authorship, and domain curation) that puts your knowledge to use on problems that matter.
Tasks are drawn from actual deployment scenarios in legal, healthcare, and finance — not synthetic toy problems. Your professional background is the qualification, not a bonus.
Every evaluation follows a versioned rubric with mandatory, optional, and negative criteria. You’ll know exactly what’s being measured and why — no ambiguous instructions.
Human Edge applies conflict checks at the panel assembly stage. Your independence is protected and documented — a requirement for the audit-grade evidence our clients depend on.
Evaluation tasks are designed for professionals with domain expertise. Work is asynchronous and project-based — engage at the level and pace that suits your schedule.
Every judgment you contribute is traceable, rationale-documented, and included in the approval packs governance teams rely on. This is credentialed professional evaluation — not crowdwork.
What you'll do
Expert judgment, applied across the AI data lifecycle
Human Edge specialists don't just assess AI outputs — they author the tasks, scenarios, and reference material that make evaluation possible in the first place. Every engagement requires the depth of your domain expertise, not just familiarity with it.
Design original prompts, edge cases, and adversarial scenarios that stress-test frontier models in your domain, the raw material evaluation itself depends on
Score AI outputs against mandatory, optional, and negative criteria. Flag errors, assess reasoning quality, and document your rationale.
Author canonical reference answers with documented reasoning. Your output becomes the ground truth that trains and benchmarks frontier models.
Compare AI outputs and select the better response with structured rationale. Captures alignment signal where ground truth is comparative, not absolute.
Test AI outputs against explicit constraints: forbidden content, missing disclaimers, unsupported claims. Negative-criteria-dominant evaluation for regulated outputs.
Evaluate intermediate reasoning steps, not just final answers. Covers evidence selection, logical consistency, and process integrity across complex domain tasks.
Evaluate deployed AI systems on an ongoing basis. Catch drift, flag regressions, and contribute to re-approval packets when models update in production.
Help source, sanitize, and structure real-world domain corpora (contracts, case files, clinical notes) into permissioned datasets used for training and evaluation
What you'll do
Three steps to
your first engagement
Apply and verify
Submit your credentials and professional background. Our vetting process uses the same compliance-grade standards we’ve applied to 1M+ expert profiles over 10 years.
Calibration training
Before any live evaluation, you’ll complete training sessions on your assigned domain. We measure inter-rater agreement and train to the rubric until consistency is confirmed.
Ongoing panel continuity
High-performing evaluators are retained across project cycles. Evaluator continuity is a feature — it maintains calibration and improves signal quality over time.
