How search works
One sentence in, a ranked shortlist out. Between those two points I plan the search, read public sources live, cross-reference what they say, and attach the reasoning to every result. You watch each step as it runs.
1. You ask
Plain English is the whole query language. “Staff backend engineers in NYC who shipped Rust in production” is a complete query - no boolean operators, no filter panels. Follow-ups refine the same search: narrow by industry, broaden the geography, ask for similar profiles.
2. I plan
I break the ask into concrete sub-searches and decide which sources can answer each one: GitHub for shipped code, public LinkedIn and Crunchbase records for roles and companies, the open web for everything else.
3. I read sources live
Sources are read at search time, not from a stale database export. That means a person’s current role, a company’s latest round, a repository’s recent activity - as of now. The steps stream into the conversation while the search runs, so you always see what I’m reading and why.
4. I rank and explain
Candidates from different sources are cross-referenced and deduplicated, then ranked against what you actually asked for. Every result ships with the reasoning behind it - the public evidence that made it a match. No black-box scores.
5. You act
From the shortlist you can ask me to draft outreach in each person’s language, keep refining, or publish the search so others can see the full result set.
What a search costs
Each search costs credits in proportion to the work it takes: quick lookups cost a credit or two, deep multi-step research with web browsing costs more. Credits are reserved up front, so a search never overdrafts your balance. Full mechanics in Credits and pricing.
Try it on the search you came here for
Stop building boolean strings. Just describe the person.
Type one sentence. I plan the search, read GitHub, public LinkedIn and Crunchbase records, and the open web as it is right now, and hand back a ranked list with the reason next to every name.
01Describe them
One plain sentence. Role, city, stack, stage, whatever matters to you.
02I read the web live
GitHub, public LinkedIn and Crunchbase records, the open web. Not a database that went stale last quarter.
03You read the shortlist
Ranked, with the reasoning under every name. Open a profile, ask a follow-up, narrow it down.
- Staff backend engineers in NYC who shipped Rust in production
- Series A fintechs in SF under 50 people, growing headcount this year
- Maintainers of fast-growing Rust web frameworks on GitHub
- No boolean, no filters, no seat to buy. One box.
- Read at search time, so a profile updated yesterday counts today.
- Every step visible as it runs, every name with its reason.
500 free credits on sign-up. No card, no demo call. See real searches.