Give your coding agent a systematic way to explore data.
Search trillions of data combinations for pennies, rank the patterns worth investigating, and carry the evidence through to the report.
Finder run
Searched 147T row-pattern combinations across 194M Medicaid rows, then ranked the evidence.
HCBS volume explains the largest share of Medicaid growth
$38.8B of the $90.1B increase concentrated in home and community-based services.
Provider billing complexity marks the strongest segment
High servicing-to-billing ratios isolate agency-based care patterns missed by flat summaries.
Which state policy changes explain the remaining variance?
Finder leaves open questions explicit instead of smoothing them into a generic answer.
Stop making agents explore data one query at a time.
Coding agents are good at context, SQL, and synthesis. But exploratory analysis gets expensive when the agent has to guess the next cut, run a query, read the result, and repeat.
Finder searches the data space directly. It tests combinations of fields and thresholds to surface specific segments: not just a single-filter alert, but the multi-condition drivers, anomalies, and interactions that show where to investigate next.
Ask
Open-ended business question
Search
Trillions of candidate patterns
Surface
Specific multi-condition anomalies
Report
Evidence and caveats preserved
What changes when your agent has Finder.
Without Finder, an agent explores by guessing the next query. With Finder, it searches the data space, surfaces specific multi-condition patterns, and hands the agent ranked evidence.
Agent alone
- Writes SQL from the prompt
- Tests obvious cuts one at a time
- Stops when an answer seems plausible
- Misses combinations it never thought to ask for
Agent + Finder
- Searches trillions of candidate patterns
- Finds specific multi-condition anomalies
- Ranks by evidence, scale, and usefulness
- Carries caveats into the report
Example pattern
HCPCS = H0036 + high claims + low beneficiaries
The output is not a generic anomaly alert. It is a specific segment your agent can investigate, validate, explain, and cite.
A toolkit for agent-native analysis.
Finder gives agents the search engine. DeepWork keeps long runs on task. The CLI bundles them for local use; the enterprise platform adds governed workflows, writeback, and controls.
Pattern discovery
Finder
Gives your agent a cheaper, systematic way to search data, rank patterns, and start analysis from evidence.
Reliable agent runs
DeepWork
Keeps long-running analysis on task with procedures, artifacts, quality gates, and reviewable handoffs.
Coding-agent customization
Unsupervised CLI
Launch Claude Code with Finder, DeepWork, and custom data-analysis tools and prompts.
Coming soon to Codex, OpenClaw, and other harnesses.
Governed deployment
Enterprise Platform
A managed environment for analysis with shared KPI definitions, governed workflows, writeback, auditability, and enterprise controls.
Enterprise-proven pattern discovery.
The technology behind Finder has already searched governed warehouse data for specific segments, estimated impact, decision workflows, and source-backed evidence.
Customers have found $1B+ in value with Unsupervised analytics technology.
AT&T identified more than $100M in opportunities with automated pattern discovery.
Unsupervised was named a Representative Vendor in Gartner Market Guides for agentic analytics for two years.
DeepWork reduced Claude Code errors by 19% on the AgentIF-OneDay benchmark.
Request the developer preview.
Launch Claude Code with Finder, DeepWork, and data-analysis defaults. Run analysis locally in the agent workflow you already use.
Join the list for Finder, DeepWork, and the Unsupervised CLI.