Most teams ship agents without knowing if they work or what they cost to run. Mercor builds evals to measure both.
The era of evals
Evals are the product spec for agents — the only rigorous way to answer three questions.
Case studies
Vetted finance experts turned expense, accounting, and approval workflows into a repeatable eval suite — so every agent release ships with evidence instead of intuition.
Senior engineers turned real pull requests, bug fixes, and refactors into a repeatable benchmark, so every model change is graded on production code instead of toy problems.
Working together
Embed our experts, run live production rubrics, or build an APEX benchmark. Every path runs on the same expert methodology.
You direct the work; we source, vet, and embed vetted domain experts alongside your team.
Live evals on your deployed agent and real traffic, scored against expert-built pass/fail criteria.
Offline benchmarks in expert-built simulated worlds. Run any model and see exactly where it breaks.
Cost x Performance
Once your eval is running, every model lands on one price–performance frontier for your workload — so you can pick the cheapest one that clears your bar.
The model that clears your bar for the least cost.
Right-size reasoning and context. Stop overpaying.
Each dot is a model on your workload. Pick the cheapest one that clears your bar.
Why Mercor
The same methodology every frontier lab relies on, now applied to your agents.
The largest and most diverse expert talent network in the world.
We build evals for the frontier labs. The processes, rubrics, and tooling are the same ones we use for your evals.
Our operators operate in high-intensity environments serving the most demanding customers in the world.
From first conversation to a reusable eval suite you own, in four to six weeks.
An eval is a rigorous, repeatable test of what your agent can actually do on your workload. It's a structured suite of tasks, rubrics, and scoring that tells you whether your agent works, which model and configuration to run, and what each option costs.
Both customer-facing and internal agents. You get the same eval expertise the biggest frontier labs rely on, applied to your product, with proven coverage across finance, support, commerce, code, and operations for enterprise and application-layer teams.
Yes. You see the full price–performance frontier, so you can choose the model that clears your quality bar for the least cost, right-size reasoning and context to stop overpaying, and pinpoint which tools and context genuinely improve results.
Yes. Post-training ROI is a core use case. You'll know whether fine-tuning your own model actually pays off before you invest in it.
You're working with the same team and methodology behind the evals run with major AI labs, backed by the largest vetted expert network in the AI economy. That’s 5M+ experts, 200k+ trained eval authors, 300+ professional domains and the rubrics and tooling refined at the frontier.
Two ways, from embedded experts to fully managed delivery: expert staffing (you direct the work while we source, vet, and embed the experts) and task-based pricing (we deliver validated evals end to end, priced per task rather than per head, as production rubrics or APEX benchmarks).
Less than six weeks from first conversation to a reusable eval suite built for your team.
Yes. You keep a reusable suite built for your team, not a one-off report.
Production rubrics run live against your deployed agent and real traffic, so scores track what users actually experience. APEX benchmarks run offline in an expert-built simulated world. It is a fixed, repeatable set to compare models and configurations before you ship. Most teams use both.
Yes. APEX benchmarks are purpose-built for your domain, with expert-authored worlds and tasks that mirror the work your agent does. It is the same standard the frontier labs run, applied to your product.