Before a team trusts an answer from an AI system, someone asks where the data came from and who changed it along the way. Lineage and quality tools that work across warehouses, applications, and spreadsheets can answer that without a months-long cataloging project. We want to meet founders who have made this work inside a messy environment.

AI tools now ask for access that people never needed, so permissions that worked for a handful of analysts stop working at scale. We're interested in founders who turn policy into controls that apply across systems, with approvals and a record of who used what.

Privacy, retention, and residency rules vary by region and industry, and audits ask for evidence on short notice. We like products that make that evidence a byproduct of normal work. Parakeet Risk takes this approach for manufacturers, with a general ledger that unifies governance, risk, and compliance.

Every industry has its own data trouble: records spread across several systems, definitions that differ by team, files nobody owns. If you're working on one of those, tell us what you're seeing.