Public signals in. Named projects out.
No black box. We point AI at the public web and get back the real projects inside your accounts: grouped by theme, with the people on them and the evidence behind each.
- Step 01
We read the public web
Public professional signals across the market: what teams are hiring for, building, and writing about. Public sources only, nothing private, nothing behind a login.
- Step 02
AI reconstructs the real projects
Our models turn those signals into named projects, grouped by theme and linked back to the evidence. Not a black-box score; you can see the sources.
- Step 03
You get the projects, and the people
The real projects inside each account, who's driving them, and a signal the moment something changes. Ready to act on.
Depth is a function of focus
You can't reconstruct a real, named project for millions of companies. The economics force you back to generic patterns. That's the trade every coverage tool makes. We made the opposite one: start narrow, go deep, and let the named-project layer become possible.
We grow by replicating that depth in each new market, not by chasing coverage and diluting it.
Real depth on a focused set of accounts.
The same depth, market by market. The method travels; the standard doesn't drop.
Private by design, access by approval
We take confidentiality seriously, on both sides of the table.
You control the reveal
People stay anonymous by default. Identity is revealed only when you choose to spend a credit on it.
Public sources only
We work from public professional signals, never private data or anything behind a login.
Approval-gated access
Access is reviewed and approved per account. We keep the room intentionally small.
See the real projects inside your accounts
Request access. Every request is reviewed before it's approved. We keep the room small on purpose.