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.
AI suggestion
Glow Highlighter Palette, $85
Is this a good gift for your friend?
Yes
No
Glimma AI
Why not?
Participant
She never wears highlighter — I’d pick a lip set.
Participants rate each AI response, and Glimma asks what fell short.
Prompt
“Find me a makeup gift for my friend, 25, under $100”
Failed response
Glow Highlighter Palette, $85
“She never wears highlighter — I’d pick a lip set.”
Golden answer
Lip and gloss gift set, $78
Every failed answer gets the answer users actually wanted.
Before
With golden dataset
Score every version on the same rubric and track the trend.
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.