User evals
Evaluate AI features with your users across real tasks. Observe how they interact with AI and see if it actually helps them solve their problems.
A response can be accurate and still feel confusing, unhelpful, untrustworthy, or hard to act on. User evals show whether the experience actually works for the people it was built for — and why.
The people using your product bring context, expectations, habits, and goals that no benchmark can fully reproduce.
01
Move beyond simple pass/fail results. Collect detailed user feedback that explains where the experience falls short and what could improve it.
Would you send this AI-generated email?
Yes
No
Glimma AI
Why wouldn’t you send it as is?
02
Turn human judgment into golden datasets that help calibrate and improve your automated evals over time.
User prompt
AI response
User verdict
Golden answer
User prompt
“Find me a makeup gift for my friend, 25, under $100”
AI response
Glow Highlighter Palette, $85
User verdict
FailGolden answer
Lip and gloss gift set, $78
03
Evaluate each product version against the rubrics, so you can see whether the experience is actually improving over time.
Define the task and choose the dimensions that matter most — such as usefulness, trust, clarity, or your own custom criteria.
Bring your own participants or recruit your target audience through our research partners.
Participants use your product naturally, with their own goals, prompts, and behavior. They rate the experience while Glimma asks adaptive follow-up questions to uncover the “why” behind each score.
Glimma combines quantitative scores with qualitative feedback, recordings, and transcripts to surface patterns, failure modes, and clear opportunities to improve the experience.
Turn human ratings and rationales into a structured golden dataset your ML team can use to calibrate and improve automated evals.
We handle the participants, the moderation and the scoring.