Job matching treats people as keyword lists. I built a skill graph instead.
Traitprint maps your real capabilities to a structured skill taxonomy, then matches you directly against ATS job data — bypassing job boards entirely.
Try the BetaThe Interesting Problem
Resumes are lossy compression of a career
The standard job search pipeline is broken in a specific, fixable way: it reduces people to keyword lists. You write a resume, a job description lists requirements, and a keyword matcher decides if there's overlap. A project manager who spent three years building cross-functional alignment processes gets filtered out because the job description says "stakeholder management" and their resume says "cross-team coordination."
The fix requires two things. First, a structured skill taxonomy that understands relationships between competencies — not just string matching but graph-level reasoning about what skills are adjacent, overlapping, or complementary. The O*NET taxonomy from the Department of Labor provides this: 500+ validated occupational skills in a hierarchical structure.
Second, you need a better way to extract skills from people than asking them to self-report on a form. People are terrible at inventorying their own skills. Socratic coaching — asking targeted follow-up questions about specific experiences — surfaces capabilities that self-assessment misses entirely.
How It Works
From unstructured experience to structured skill graph to matched roles.
Voice/Text Input | v [Socratic AI Coach] ── targeted questions ──> skill extraction | v [O*NET Taxonomy Mapper] ── 500+ skills ──> structured Traitprint | v [ATS Job Feed] ── Greenhouse, Lever, Ashby, Workable, Workday | v [Skill Graph Matcher] ── graph distance, not keywords ──> ranked matches | v Swipe Interface ──> preference learning ──> better matches over time
Discover
AI coaching interviews extract skills through conversation, not forms. It asks the right questions to uncover expertise you'd never put on a resume.
Map
Skills are mapped to O*NET — the same taxonomy employers use. This creates a shared language between what you can do and what they need.
Match
Jobs from ATS APIs are scored against your skill graph. Graph-distance matching finds roles that keyword search would miss.
What Makes It Different
The technical decisions that shape how Traitprint works.
O*NET Skill Taxonomy
500+ validated competencies from the Department of Labor's occupational database. Skills are structured, scored, and mapped to the same framework employers use to write job descriptions.
Socratic AI Coaching
Instead of asking users to self-assess, the AI conducts targeted interviews that draw out real expertise. Voice or text input — it finds skills people didn't know they had.
Direct ATS Integration
Jobs pulled straight from Greenhouse, Lever, Ashby, Workable, and Workday APIs. No scraped listings, no aggregators, no dead links — direct from the source.
Skill Graph Matching
Matching happens at the skill-graph level, not keyword level. A project manager with 'stakeholder alignment' experience matches roles asking for 'cross-functional leadership' — because the taxonomy understands they're related.
Swipe-Based Review
Matched jobs surface in a swipe interface. Right for interested, left to pass. Preferences feed back into the matching algorithm, sharpening results over time.
Targeted Resume Generation
Resumes generated from your Traitprint, tailored per role. Each version highlights the skills and experience that matter most for that specific position.
Direct ATS Integration
Jobs pulled directly from the applicant tracking systems companies use. No scraped listings, no aggregators.
Built With
Try it yourself
Traitprint is in public beta. Create your skill profile and see how graph-based matching compares to keyword search.
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