Eval directory
Evals for Mercor
8 evaluation packs covering adversarial robustness, safety gates, workflow quality, and operator-level checks for Mercor AI products.
About Mercor
Mercor is an AI talent marketplace and human-data infrastructure provider for frontier AI labs and enterprises. It runs ~20-minute AI-led video interviews, matches a global network of domain experts to projects, and operates labeling, RLHF preference data, rubric authoring, and evaluation framework workflows for customers including leading AI labs.
How complete this published benchmark library is across datasets, metrics, rubrics, use-case maps, and pack context. This is library coverage, not an agent performance score.
Test datasets
8/8 packs
Scoring metrics
0/8 packs
Judge rubrics
8/8 packs
Use-case maps
0/8 packs
Pack context
8/8 packs
Available eval packs for Mercor
8 packs ready to run.
Ai Led Interviews And Scoring
Evaluates Mercor's AI-led Interviews & Scoring across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's AI Talent Marketplace & Data Labeling eval coverage.
Candidate Sourcing And Matching
Evaluates Mercor's Candidate Sourcing & Matching across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's AI Talent Marketplace & Data Labeling eval coverage.
Customer Lab Data Delivery
Evaluates Mercor's Customer / Lab Data Delivery across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's AI Talent Marketplace & Data Labeling eval coverage.
Expert Contractor Onboarding
Evaluates Mercor's Expert / Contractor Onboarding across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's AI Talent Marketplace & Data Labeling eval coverage.
Labeling And Rlhf Workflows
Evaluates Mercor's Labeling & RLHF Workflows across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's AI Talent Marketplace & Data Labeling eval coverage.
Operations And Payments
Evaluates Mercor's Operations & Payments across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's AI Talent Marketplace & Data Labeling eval coverage.
Quality Control And Calibration
Evaluates Mercor's Quality Control & Calibration across 9 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's AI Talent Marketplace & Data Labeling eval coverage.
Safety Ethics And Governance
Evaluates Mercor's Safety, Ethics & Governance across 10 scenario-based test cases, each graded against an expected-behavior rubric by an LLM judge, from Corsac's AI Talent Marketplace & Data Labeling eval coverage.
Why eval Mercor AI
Mercor's AI features ship behind brand promises about accuracy, safety, and reliability. Buyers and integrators need to know those promises hold up under adversarial prompts, edge-case workflows, and the long tail of real customer inputs — not just the demo path.
The Corsac eval library for Mercor measures four dimensions teams care about most when deploying ai platform agents:
- Adversarial robustness — does the agent resist prompt injection, jailbreaks, and social-engineering attempts?
- Workflow quality— does it complete the task buyers were shown in the demo, on inputs that don't look like the demo?
- Safety gates — does it escalate or refuse when it should, and only then?
- Operator quality — does it preserve analyst trust by surfacing the right context at the right time?
Every eval pack above is hand-authored against Mercor's public product surface and runnable in Corsac with your own data.