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Feature · Upsolve Golden Questions

Teach your agent the right answer, and know when it's unsure.

Save the questions your agent must get right, with the SQL you trust. Upsolve uses them as test cases and references, and scores every answer's confidence before it reaches a user.

Test casesConfidence scoreAnswer threshold
New · Launch Month day 10, Fri 9 Oct 2026 · Upvote on Product Hunt →
SAVE AS GOLDEN QUESTIONVERIFIED
Upsolve Save as Golden Question dialog with the question about the worst vendors and its expected SQL
01 / The problem

Your agent answers the same question differently every time.

01

Words like "worst vendor" mean something specific at your company, and the agent has to guess.

02

Good answers from real users disappear into chat history instead of teaching the agent.

03

Every answer reaches the user looking equally sure, even when the agent reasoned its way to a guess.

02 / How it works

From setup to production in three steps

01

Find a good answer

Open a past conversation in observability and check the question, the SQL and the chart.

02

Save it as a golden question

Keep the SQL as it is, or edit it first. For example, rank the worst vendors by spend only, not by order count.

03

Set a confidence threshold

Every answer gets a confidence score. Raise the threshold and low-confidence answers are held back from end users.

03 / What changes

What changes with Upsolve Golden Questions

Without Upsolve Golden Questions

A vague question gets a plausible answer, and nobody can tell a verified number from a guess.

With Upsolve Golden Questions

Verified questions guide the agent, and each answer carries a confidence score that can stop weak answers reaching users.

04 / What you get

Everything that ships with Golden Questions

REPOSITORY

Golden question repository

A growing library of questions your agent should answer consistently correctly.

TESTS

Test cases for your agent

Check the agent still gets your golden questions right after every change.

CONFIDENCE

Confidence score

Based on matching golden questions, whether the fetched schemas and columns fit the question, and whether a good chart was produced.

FILTER

Answer filtering

All answers go through by default. Sensitive teams can set a high threshold so users only see high-quality results.

05 / Where it fits

One layer of a closed learning loop

Upsolve builds the whole stack for data agents that stay accurate in production. Every conversation feeds the next improvement.

01
Ontology
Your data described clearly. Permissions enforced deterministically, not delegated to the agent.
02
Agent harness
Snappy, reliable, accurate. Learns from real interactions and updates its skills and memory.
03
Distribution
Your product, your Slack channels, Claude. Go where your users already are.
04
Improvement loop
Live evals on real usage find the gaps, then you harden the context to close them.
This feature
06 / Launch Month

Part of Upsolve Launch Month

See all fourteen launches →
07 / FAQ

Common questions

From real conversations. Open a chat in observability, review the SQL and save it, editing it first if needed.

Whether the answer matched golden questions and how correct they were, whether the schemas and columns fetched fit the question, and whether a good chart was produced.

No. All answers go through by default. You choose a threshold if you want to filter weak answers out.

Can't find your answer? Get in touch.

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