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Model & Agent Evaluation

Measure what benchmarks can’t.

Automated metrics tell you a model changed. Human evaluation tells you whether it got better — for real users, on the dimensions you care about. OmniTech runs rigorous, calibrated human evaluation across models, prompts and agent trajectories.

Evaluation methods

Rigorous human judgment, applied consistently.

Rubric-based scoring

Multi-dimensional scoring against rubrics you define — helpfulness, correctness, tone, safety, format adherence and more.

Pairwise comparison

Side-by-side A/B judgments to rank models or checkpoints, with forced rationale and tie-handling policies.

Factuality & groundedness

Claim-level verification against sources: is it true, is it supported, and does it cite what it should?

Hallucination analysis

Categorize and rate fabrications, unsupported claims and overconfidence, with taxonomies your team can act on.

Benchmark & release support

Human evaluation tied to your eval sets and release cadence, so every version gets a comparable read.

Model comparison

Head-to-head evaluation across your model and alternatives, with statistically legible reporting.

Agent & tool-use evaluation

Judgment for systems that take actions.

Agentic systems don’t just answer — they plan, call tools and take multi-step actions. Evaluating them needs humans who can follow a trajectory and judge whether each step, and the whole, was right.

Trajectory assessment

Step-by-step review of an agent’s plan and actions — was each decision reasonable given what it knew at the time?

Tool-call correctness

Did the agent call the right tool, with the right arguments, and interpret the result correctly?

Task completion

Judgment on whether the end-to-end task actually succeeded — not just whether it looked done.

Long-horizon & multi-turn

Evaluation of coherence, recovery from errors and goal-tracking across long, multi-turn interactions.

Trust the numbers

Evaluation you can defend in a research review.

A quality signal is only useful if it’s reliable. We calibrate evaluators, embed gold checks, track inter-rater agreement, and route disagreement to senior adjudication — so your scores reflect the model, not the mood of the crowd.

How quality is measured

Signals we report

Inter-annotator agreement
Consistency between evaluators
per task
Gold-task accuracy
Performance on hidden checks
per evaluator
Adjudication rate
Share escalated to seniors
per batch
Turnaround
Against agreed SLA
tracked

We report methodology and the signals above. We don’t publish invented accuracy figures — your numbers come from your program.

Get started

Run a calibrated human evaluation.

Send us your rubric or let us help build one. We’ll qualify evaluators, calibrate them, and return scores you can trust.