Automated evaluations that catch errors before they reach a decision-maker - so you can ship data agents your business will actually trust.
01
build ground truth
Your team curates the expected answers to your most important questions - revenue, churn, pipeline. These become your benchmarks.
02
run evaluations
dardar tests your data agent against those benchmarks after every agent update or schema change. No manual spot-checking.
03
gaps and regressions surface
See exactly where answers diverge from ground truth, and which query types aren't covered at all - before a bad number reaches a stakeholder.
04
fix the root cause
Update documentation, schema definitions, or context. Re-run evaluations to confirm. Your benchmark suite keeps pace as your data and agents evolve.
Evaluations run against your data agent - so regressions surface in minutes, not after someone points out an error in your presentation.
"What is our ARR from APAC?"
Agent
$14.2M
Ground truth
$12.8M
Catch regressions early
Evals run automatically on every agent or model update. Failures surface before they reach a stakeholder.
"What is our average deal size this quarter?"
Agent
$47K
Ground truth
$52K
Ground truth you own
Expected answers are curated by your team - not generated by another model. Trust is grounded in fact.
"Does the eval suite cover cohort churn queries?"
Query share
23% of analyst queries
Suggested
4 benchmark evals
Coverage that grows
See which query types are tested and which aren't. dardar surfaces gaps based on what your team actually asks.
dardar reads your dbt models, metric definitions, and documentation - so answers reference your business logic, not generic SQL.

Who are our top customers this quarter?
Acme Corp
$284K
+22% vs last quarter
Bright Labs
$201K
flat quarter-over-quarter
Nexus Inc
$178K
new this quarter
These three account for 31% of Q1 revenue. Acme's growth is from a seat expansion in February - they're now your fastest-growing account.