Agentic data analysis · Commercially available

The evidence layer for data teams.

Finder for Teams is where we learned to control agents in production. It finds the patterns moving your KPIs and gives your analysts the evidence to act on them.

How it works

Connect the warehouse

Databricks, Snowflake, BigQuery, Redshift. Finder learns your data model and works with complex, multi-table data automatically.

Search for what moves your KPIs

Automated pattern discovery across the full data, organized by business outcomes, not dashboards. Every insight shows its segment conditions, never a black box.

Review, then act

Patterns arrive ranked by estimated financial impact, with evidence an analyst reviews before anyone acts, then move into opportunities, reports, and record-level workflows.

Evidence

What it has found in production.

$100M+

in estimated value from insights AT&T put into action

$1B+

in actionable insights found by customers since 2021

144x

faster than manual analysis on deep research runs

20 min vs 2–3 days

“Unsupervised’s AI Data Analysts have delivered strong ROI—improving our key metrics while empowering our team with faster, smarter access to data insights.”

Mark Austin · VP Data Science, AT&T

Read the case study →

Artifact

What an insight looks like.

insight · from the published HHS run

segment organizationally complex, high-volume, low-cost services
kpi mean spending growth 179,156% — explosive growth from small bases
evidence key driver in 6 of the top 10 patterns by KS score
conditions segment definition attached, human-readable
caveats fee-for-service data only
Unsupervised.com — March 2026

Segment, lift, scale, evidence, caveats: every insight carries all five, so review is fast and action is defensible.

Next step

See it on your data.