Diligence · AI / ML · Pre-seed–Series B
AI & machine learning diligence, cited to its source.
AI companies attract heavy funding and fast hiring, so the diligence challenge is separating genuine technical depth from narrative. The fused read pairs patent and hiring upside with hard checks on founder history and IP provenance.
Deterministic, re-runnable diligence scoring.
What drives the read here
The questions that decide a proceed or a pass.
- Patent filings and technical hiring separate real capability from positioning.
- IP-ownership and prior-employer disputes are a recurring litigation risk for AI teams.
- Rapid, large raises make Form D and insider filings especially informative on the cap table.
- Adverse-media monitoring catches model-safety and data-provenance controversies early.
Grounded in public data
For ai / ml, the verdict draws primarily on SEC EDGAR, USPTO, CourtListener, GDELT, OpenCorporates — every finding links back to its source record with a snapshot date, so your team and your IC can re-verify it. See the full data sources and compare other sectors.
See a cited verdict for ai / ml.
Name a company or founder. We'll return a fully cited risk × upside verdict you can trace, line by line, back to source documents — yours to keep monitoring, defend at IC, or share with an LP.