Evaluate AI against real work, not only generic benchmarks
We evaluate not only whether a response appears plausible, but whether it would be considered usable by someone familiar with the underlying work.
Evaluation Services
Testing designed around how outputs are actually used, not just how they read.
Realistic Benchmark Creation
Evaluation sets built from real tasks in your domain, not generic public leaderboards.
Rubric-Based Grading
Consistent scoring criteria applied by practitioners and domain-aware reviewers.
Agent & Workflow Testing
Checking whether an agent completes a multi-step task correctly, not just whether one reply sounds right.
Model Comparison
Head-to-head grading across model versions or vendors on the same task set.
Failure Categorization
Grouping recurring failure patterns (hallucination, inconsistency, wrong assumptions) so fixes can be prioritized.
Multilingual & Cross-Market Evaluation
Testing whether outputs hold up across languages, not just whether they translate literally.
What You Get
A typical evaluation engagement delivers a concrete, reusable set of artifacts, not just a score.
Scope, including whether an engagement covers security-relevant or regulated behavior, is defined per project — we don't claim formal security audits or regulatory certification as a default part of this service.
Ready to Evaluate Your Model?
Tell us what the model needs to prove, and we'll help design the evaluation set.