Four buyers, one operating standard

Frontier AI Labs

Evaluation demand scales with model capability, not against it.

Labs no longer buy bounding boxes. They buy expert evaluations, RLHF from skilled raters, agentic-task benchmarking and code review. Work that rewards small, trained, accountable teams over anonymous crowds.

What they buy

• Expert-tier evaluation
• Agent benchmark programs
• RLHF at calibrated agreement
• Red-team prompt sets

How it starts

Vendor registration and long-cycle relationship building, entering through evaluation and benchmark niches.

AI Data Platforms

Revenue grows faster than trained-contributor supply. We are inventory, not competition.

Every prime platform faces the same operational constraint: demand spikes outpace their vetted bench. A managed team that arrives pre-vetted, pre-calibrated and QA-wrapped absorbs the spike without diluting their quality story.

What they buy

• Subcontract capacity
• White-label managed pods
• Overflow delivery
• Independent QA layers

How it starts

Managed pods under your brand, your tooling, your client relationship.

Evaluation Tooling Companies

Harness builders need human graders. Neither of us wants to become the other.

Companies building evaluation infrastructure need a human-grading partner who works inside their stack rather than selling a competing platform. We are deliberately tooling-agnostic.

What they buy

• Human grading inside your harness
• Gold-set construction
• Rubric design
• Grader calibration

How it starts

Co-sell arrangements. Your harness, our graders.

Enterprise AI Teams

Internal AI teams need evaluation discipline without building an evaluation org.

Teams shipping AI products inside large enterprises need domain-expert evaluation, safety review and dataset verification, but cannot justify a permanent internal review function.

What they buy

• Domain-expert evaluation
• Safety and factuality review
• Dataset verification
• Model regression testing

How it starts

Inbound via published benchmark work and referrals.