See every step your data agent took, and fix it.
Every conversation, trace, SQL query and skill call your agent makes, in one place. Live LLM-as-judge evals flag wrong answers, lazy responses, empty results and frustrated users, so you can fix the context before trust breaks.
Feature 06 of 14 · The Complete Agent Stack →
Data agents don't fail loudly. They fail quietly.
A slightly wrong number looks exactly like a right one.
Users who get a bad answer ask again, then stop using the agent.
Without traces, builders can't tell whether the problem is the data, the context or the question.
From setup to production in three steps
See every session
The agent chat history shows every user, question, eval result and cost.
Trace every step
Open any session to see RAG retrieval, the skill used, the SQL, validation and the chart.
Close the loop
When an eval flags a problem, fix the prompt, skill or data model and watch the next conversations improve.
What changes with Upsolve Observability
Wrong numbers and frustrated users go unnoticed until someone stops trusting the agent.
Every session is traced and graded on real usage, so you see the failure and the fix in one place.
Everything that ships with Observability
Live evals on real usage
Answer correctness, agent laziness, null or empty results, chart failures and user frustration.
Full step-by-step traces
The exact SQL, RAG sources and tool calls behind every answer.
Cost per trace
See spend, charts generated and errors for each individual trace.
One view across surfaces
Embedded, Slack and Claude conversations all land in the same history.
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.
One of fourteen features in The Complete Agent Stack
Common questions
Signals like a user repeating the same request because they didn't get what they expected.
On real conversations as they happen, so you see how the agent performs for actual users.
Yes. Every deployment surface writes to the same agent chat history.
Can't find your answer? Get in touch.