Hire engineers without reading 500 5 résumés.
ResumeDB writes the JD, runs the apply page, and screens every applicant with a pipeline of AI agents. You get a ranked shortlist; candidates get an answer in minutes.
Free to start · no credit card · GitHub + LinkedIn enrichment included
- resume.extracted7y · Python · Go · Kafka
- linkedin.verified4 of 4 roles confirmed
- github.repos2 useful · 1 vibe_coded
- jd.match0.87 · Kafka, distributed systems
- shortlist.queuedinterview slot reserved
From brief to shortlist, while you're in another meeting.
Four stages. You touch one and four; agents do the rest.
- 01Recruiter
Brief in
Paste a brief. We draft a full JD with role-specific custom questions in seconds.
brief:“mid-senior backend eng, Go or Python, distributed systems, remote OK” - 02Candidate
Public apply page
Share /apply/your-job. A 4-step intake captures the resume, profile, GitHub, and your custom questions.
/apply/backend-engresume → fields → repos → questions - 03Mastra agents
Pipeline runs
Five agents run on every application, end-to-end, in seconds.
extractcredibilityreposmatchdecide - 04Both sides
Shortlist + reply
Ranked list with cited evidence on your end. A real, explained reply on theirs.
shortlisted with reason
Chat your talent pool. In English.
Hybrid retrieval with skill-synonym expansion. Every result cites the resume section it came from, so “why did this rank?” has an answer.
- Natural-language search across the whole pool
- Cited evidence per candidate, no black box
- Skill synonyms: React ⇄ Next.js, Postgres ⇄ RDS
Inbound applications stop being a chore.
Generate a JD from a brief. Share a link. Each application is screened end-to-end before it lands in your queue.
- Auto-generated JD with role-specific custom questions
- Auto-shortlist or auto-reject, with a real reason
- Candidates get an explained reply, not a void
Senior Backend Engineer
Distributed systems, Go or Python. You'll own the streaming ingest pipeline serving 40M events/day.
- S. Chen shortlist
- M. Okafor shortlist
- T. Vasquez passed
- K. Iyer shortlist
The repo analyzer that flags AI slop.
Each repo is verdicted as useful, basic, or vibe_coded. Paired with a LinkedIn cross-check, inflated experience stops slipping through.
- GitHub repo quality verdicts per candidate
- Credibility judge catches inflated claims
- Evidence trail you can audit, not just trust
- usefulkafka-connect-clickhouse8 contributors · 87% test coverage · Go
- usefulgo-rate-limiterSolo · clean structure · benchmarked
- vibe_codedtodo-app-llm-rebuildSingle commit · LLM-generated boilerplate
Trade your applicant pile for a shortlist.
- Open 47 PDFs in tabs to skim
- Boolean filters on JD keywords
- Manually verify LinkedIn for each shortlist
- Auto-rejection emails two weeks later
- Re-discover the same candidate next quarter
- Brief in. Apply page out. Done in two clicks.
- Chat the pool: 'find me senior Kafka people, US-based'
- Credibility judge cross-checks every claim
- Each applicant gets a real, explained reply in minutes
- Talent pool grows with every job; searchable forever
Stop reading the bottom 90% of the pile.
Spin up your first job in five minutes. The agents handle the screening; you handle the conversations that matter.
Free tier · GitHub + LinkedIn enrichment included · cancel anytime