Human evaluation for AI models that have to be right
A trained evaluation team that reviews, ranks, and annotates model outputs for accuracy, reasoning, safety, and instruction-following, with experienced engineers for code and technical tasks.
Who this is for
Teams that need careful human judgment on model behavior, at a quality level that automated metrics can't provide.
AI labs training or fine-tuning models
Preference rankings, rubric-based grading, and red-team style probing to feed RLHF and evaluation pipelines.
Product teams shipping LLM features
Prompt and response testing against your own guidelines before and after release, so regressions are caught by people, not customers.
Teams that need technical evaluation
Code, software engineering, math, and technical-reasoning outputs judged by reviewers who can actually run and verify the work.
Data teams that need overflow capacity
A calibrated team that can pick up an existing guideline set and match your quality bar, rather than starting from zero.
What we do
Seven service lines, all delivered by the same evaluation team and QA process.
AI Model Evaluation
We review and compare AI-generated responses for accuracy, reasoning, relevance, instruction-following, and overall quality.
AI Training Data & Annotation
We create, label, review, and validate high-quality datasets used for machine learning and generative AI training.
Human Feedback & RLHF
Structured human feedback, response ranking, and preference evaluation to support reinforcement learning and model alignment.
Prompt & Response Testing
We test prompts and model responses to identify incorrect answers, hallucinations, reasoning issues, and opportunities for improvement.
AI Quality Assurance
Detailed review of AI-generated content and annotated datasets to ensure consistency, accuracy, and compliance with project requirements.
Technical AI Evaluation
Coding, software engineering, and technical-reasoning responses evaluated by experienced technical reviewers who understand the work being judged.
AI Safety & Alignment
We review AI outputs against defined safety, quality, and behavioral guidelines to help build more responsible and dependable AI systems.
How an evaluation project runs
We calibrate before we scale, and we measure agreement throughout so quality is visible, not assumed.
Guidelines & calibration
We work through your rubric with the team, grade a shared calibration set, and resolve disagreements until reviewers converge on your standard.
Pilot batch
A small batch goes through the full pipeline so you can check quality, format, and throughput before committing volume.
Production with QA sampling
Work runs in cycles. A second reviewer samples completed items, and inter-rater agreement is tracked and reported.
Reporting & feedback loop
You get structured output in your format, plus notes on guideline gaps, edge cases, and recurring model failure modes.
Frequently asked questions
Straight answers to what founders and teams usually ask before starting.
What kinds of evaluation tasks do you handle?
Pairwise and ranked preference comparisons, rubric-based scoring, factuality and hallucination checks, instruction-following review, safety and policy review, conversational quality, and technical evaluation of code and reasoning. We also create and validate annotated datasets.
How do you keep quality consistent?
Every project starts with calibration against a shared gold set. During production a second reviewer samples completed work, and we track inter-rater agreement and report it to you. Guidelines are treated as living documents and updated as edge cases surface.
Can you evaluate code and technical outputs?
Yes. Our technical reviewers are working software engineers. They run the code, check the reasoning, and judge whether an answer would hold up in a real codebase, not just whether it looks plausible.
How do you handle confidential data and models?
We sign your NDA, work inside your tooling when required, and restrict access to the reviewers assigned to the project. Data is not reused across clients.
How do we get started, and is there a minimum?
Send us the task type, rough volume, and your guidelines if they exist. We'll propose a pilot batch, usually completed within a week, and quote per item or per hour depending on the task.
Tell us what you're building
Whether it's a product to ship or a model that needs human eyes on it, tell us where you are and we'll reply with next steps.
Spanish Fork, UT 84660-1319
United States