This is one workspace for one open role. First you source it the way you did this morning, building a string, opening every profile, pasting the keepers into a sheet. Then you flip one switch and the same workspace starts sourcing on its own, narrating every move it makes.
Free credits on signup. Metered per candidate. Search your own pool on live roles.
Build the string, open six tabs, read to the last line, paste the two that survive.
Same role, same brief, same screen. You stop searching and start deciding.
Ranked, enriched candidates across channels, each with the reason it matched. You approve.
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Act 1 · by hand · you do it
Six profiles for a role that needs forty. Two are usable, and one of those was a duplicate you nearly pasted twice. This is search string one of six.
One tab at a time, read to the last line.
One recruiter, one trainer, one student, one duplicate.
For a fraction of one search string, on one channel.
The keyword string never learned what a ledger is, so the strongest candidates were the ones hiding on the last line of the profile. There are five more strings behind this one.
Build the string, open every profile, paste the keepers. The clock runs while you read.
Two usable out of six, one of them a duplicate. This was one string of six.
Act 2 · hand it over · one switch
Same role, same brief, same screen. You stop being the search engine and become the person who decides. Flip it and the workspace starts working underneath you.
The brief does not change when you flip the switch. Only the way the work gets done does. Ask in plain English, no boolean, no NOT intern. The agent takes it from there.
You keep the brief. You hand over the search.
The workspace is the agent's now. Watch it run.
Act 3 · watch it run · the agent works
Senior Backend Engineer for payments. 5+ years on Java and Spring Boot, real distributed systems, someone who has touched a ledger or settlements. Bengaluru hybrid or self-relocation. Skip agencies and trainers.
Why it matched: Maintains an open reconciliation library with idempotency keys and retry windows, the exact failure mode in your brief. The word ledger appears nowhere on her profile.
Why it matched: Refund and settlement flows at a logistics platform, and a post saying he moves in spring. You found him by hand in Act 1. It took eighteen minutes and the note was on the last line.
Why it matched: Already yours. Reached the final round on your Platform role fourteen months ago, lost to a single offer. Two duplicate records merged into one.
Why it matched: Gave a meetup talk on double-entry ledgers at scale. The talk is evidence, the headline is marketing. Flagged: Bengaluru hybrid is a real question to ask her.
Why it matched: Two engineers on your team worked with him at a previous employer, so a warm intro is available before any cold message. Lighter on payments than the four above, ranked accordingly.
The agent ranks and explains. It never sends outreach on its own. Approved candidates hand off to the AI Calling Agent, which checks their job-search intent and collects an updated resume, then the AI Interviewer. You keep the final call.
Approved for outreachSample data. Names, profiles and results shown here are illustrative, not real people. Run it on your own roles and channels.
The agent sweeps every channel, sets aside the noise with a reason, and merges the duplicates.
Five ranked candidates, each with the evidence it matched on. You approve who gets contacted.
The AI Sourcing Agent works a requisition the way an expert recruiter would, without the manual toil. Describe the role in plain English and it searches across sources at once: your own internal resume database of past applicants, public candidate profiles surfaced through Google X-ray searches, and sources such as GitHub. It reads the full context of every profile, so it surfaces people whose experience fits even when their wording does not match yours.
It ranks the shortlist on capability, not keywords, sets aside recruiters, trainers and other noise with the reason kept on file, merges duplicate records, and attaches an evidence-based reason to every candidate it keeps. It never sends outreach on its own. You approve who gets contacted, and approved candidates hand off to the AI Calling Agent, which calls them, checks the intent of their job search and collects an updated resume autonomously, then they flow into interviews and your ATS.
Describe the role or paste the JD. No boolean strings, no exclusion syntax to maintain.
Your internal talent pool, public candidate profiles via Google X-ray search, and sources like GitHub, swept in parallel.
Past applicants and silver medalists resurface the moment a matching role opens.
Every candidate carries the reason it matched, drawn from what the profile actually shows.
Recruiters, trainers and duplicates are held with the reasoning kept on file, not silently dropped.
The agent ranks and explains. It never sends outreach until you approve.
Sample quotes shown for layout review. Real customer stories will replace these.
It rediscovered forty strong candidates already sitting in our talent pool. We were paying to source people we had already met.
The ranked matches come with a reason, so I can defend every outreach instead of guessing.
It works one requisition the way I would, only it does not get tired at profile ninety.
Most sourcing tools sell you access to the same crowded external databases everyone else searches. The AI Sourcing Agent starts with the asset only you own, your applicants, and makes it fully searchable, then extends outward across channels. Every candidate it surfaces carries the reason it matched.
Yes. That is the core of the reusable talent pool. The agent surfaces past applicants and previous runners-up the moment a matching role opens, so warm talent who already know your company resurface instead of starting every search from a cold start.
Yes. It sweeps your internal talent pool alongside public candidate profiles found through Google X-ray searches and sources like GitHub, then ranks everything on capability and attaches the reason and source each candidate came from.
Sourced candidates can be handed to the AI Calling Agent, which calls them autonomously, checks the intent of their job search and collects an updated resume. Interested candidates flow straight into AI interviews and your ATS with no re-entry.
Parsing is built in. Every uploaded or historical resume becomes structured data, skills, seniority, domains and progression, automatically, so a separate resume parsing tool becomes unnecessary and your whole archive is searchable.
Yes. The agent's multilingual understanding makes resumes in different languages searchable together, so one plain-English query covers your whole pool regardless of the language each resume was written in.
Yes. You can connect your ATS or HRMS or import resumes in bulk, and sourced candidates sync back through integrations and webhooks, so your system of record stays current without re-entry.
Point the AI Sourcing Agent at a live role and let it search your own pool and public sources, ranked with a reason on every match. Start free with credits on us. Humans keep the final call.
