Spend less time sourcing. More time with candidates.
Turn a client JD into a ranked pool of real profiles with fit evidence, risks to verify, and outreach starting points.
Senior backend engineer
Ranked candidate pool
Candidate A
Reach out firstGlobal-scale APIs and platform systems match the role.
Risk: startup-stage preference is unknown.
Candidate A
Senior Software Engineer at a global commerce platform
Built merchant-facing APIs and backend platform systems at global scale, directly matching the JD's API and production-systems requirement.
Risk: No public signal yet on willingness to move into a smaller team environment.
Candidate B
Staff Software Engineer at an enterprise software company
Led platform work spanning product systems, data storage, and reliability, which lines up with the JD's backend-plus-product shape.
Risk: Staff-level profile may be over-scoped for a role that still looks hands-on and execution heavy.
Your client role
Hirelix builds the sourcing brief before it searches, screens, and compares the pool.
How it works
Hirelix keeps the first pass focused: understand the role, research real people, inspect the evidence, and start outreach only after a candidate is worth it.
Start from the real role on your desk. No Boolean rebuild or long setup flow.
The agents extract must-have skills, constraints, target signals, and comparable backgrounds.
Real profiles are sourced, scored, and checked for public technical evidence in parallel.
Open the full ranked pool with a recommended shortlist, fit reasons, risks, evidence, and outreach starting points.
Features
The product is built around the work a technical headhunter needs before putting a candidate in front of a client.
Turns the client JD into role requirements, constraints, target company signals, and adjacent background patterns.
Sources around real candidate profiles instead of generating synthetic records or generic persona matches.
When you choose to research a candidate, Hirelix checks sources like GitHub, papers, technical blogs, company engineering blogs, package registries, Stack Overflow, talks, personal sites, and portfolios.
Each scan reviews targeted profiles and preserves the full ranked pool, with recommended candidates marked inside it.
Shows why the candidate fits, what might block the match, and what evidence is safe to reference.
Creates personalized outreach starting points from profile fit and candidate research. Nothing is sent automatically.
Pricing
Try one real role first. Upgrade only if the output is useful.
Run a real preview before you pay.
1 AI sourcing preview
For a technical headhunter covering a few active client roles.
per month, billed annually
For recruiters running a larger active client-role desk.
per month, billed annually
Targeted profile scans are AI sourcing budget, not a guaranteed final candidate count. Hirelix observes the pool, adjusts sourcing angles, dedupes useful profiles, and ranks the strongest candidates found within your plan budget.
Questions
Short answers for the trust checks that matter before the first candidate pool.
A.Yes. The product is built around real LinkedIn profile discovery, not synthetic candidate records.
A.When you choose to research a candidate, Hirelix checks sources like GitHub, papers, technical blogs, company engineering blogs, open-source packages, Stack Overflow, talks, personal sites, and portfolios.
A.A ranked candidate pool with recommended profiles, fit evidence, risks to verify, and personalized outreach starting points.
A.No. Hirelix drafts outreach so you can review, edit, and decide when to contact a candidate.
A.Continue from the recommended shortlist inside the ranked pool, unlock the workflow capabilities you need, and work the candidates inside the product.
For technical recruiters
Find, screen, and compare real technical profiles from a client JD, then decide who deserves a conversation.
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