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.

A reviewer studying outputs on a screen, seen from over the shoulder in a dark room
Model outputs, reviewed by people who know the domain

Start with a pilot batch

Send us your task type, rough volume and guidelines if you have them. We calibrate on a shared gold set, run a pilot batch through the full pipeline — usually within a week — and report quality and inter-rater agreement before you commit to volume. Priced per item or per hour; your NDA, your tooling, your data never reused.

Who this is for

Teams that need careful human judgment on model behavior, at a quality level that automated metrics can't provide.

01

AI labs training or fine-tuning models

Preference rankings, rubric-based grading, and red-team style probing to feed RLHF and evaluation pipelines.

02

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.

03

Teams that need technical evaluation

Code, software engineering, math, and technical-reasoning outputs judged by reviewers who can actually run and verify the work.

04

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

What every evaluation engagement includes, from calibration to reporting.

01

Guidelines & calibration

rubric design and a shared gold set before production

02

Pilot batch

a bounded first batch, usually completed within a week

03

Production evaluation

trained reviewers matched to your task type

04

QA sampling

second-reviewer checks, inter-rater agreement tracked and reported

05

Technical review

code and reasoning evaluated by working engineers who run the code

06

Reporting & feedback loop

quality reports that refine the rubric over time

How an evaluation project runs

We calibrate before we scale, and we measure agreement throughout so quality is visible, not assumed.

01

Guidelines & calibration

We work through your rubric with the team, grade a shared calibration set, and resolve disagreements until reviewers converge on your standard.

02

Pilot batch

A small batch goes through the full pipeline so you can check quality, format, and throughput before committing volume.

03

Production with QA sampling

Work runs in cycles. A second reviewer samples completed items, and inter-rater agreement is tracked and reported.

04

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.

Office1285 N Canyon Creek Pkwy #1004
Spanish Fork, UT 84660-1319
United States
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