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How we turn resumes into evaluations
Our ML models don't just parse text—they understand semantic relationships, skill clusters, and context that keyword-based screening misses.
FitToHire organizes experience into meaning.
FitToHire groups related skills, experience, and qualifications into coherent clusters — the way hiring systems should evaluate them, but don't. This turns scattered resume content into structured signals that reveal your true fit.
You’re seeing how disconnected details become evaluable context.
Semantic clustering in action
Grouping by meaning, not just keywords
Built on real evaluation data
FitToHire is grounded in large-scale hiring data — not generic language models or prompt engineering.
Its evaluation logic is derived from how roles are actually defined and screened in practice.
This is why FitToHire explains decisions instead of guessing.
Semantic Understanding
FitToHire groups related skills and experience by meaning — not just keywords.
Context Recognition
FitToHire identifies where your experience comes through clearly, weakly, or not at all.
Evidence-Based Insights
FitToHire shows exactly where your resume matches — and where screening software can't see it.
Same resume. Two evaluation paths.
Resume excerpt
Led backend development for a high-volume payments platform.
Worked closely with cloud infrastructure and data teams to improve reliability.
Language-based interpretation
Optimized to summarize and infer intent
Strong backend engineer with cloud and distributed systems experience.
FitToHire evaluation
Optimized to determine what counts
- Backend development: counted
- Cloud infrastructure: implied — needs evidence
- Distributed systems: partial
- Screening risk: elevated
Both interpretations sound reasonable. Only one is safe for evaluation.
Why FitToHire is not an LLM-based evaluation
Different tools are designed for different jobs. FitToHire is designed to evaluate.
FitToHire
Purpose-built ML system
LLM-based
General language model
Keyword
Simple text matching
Capability comparison
Groups related skills into coherent clusters
Separates signal from narrative
Produces a repeatable evaluation
Explains why a resume scores as it does
Resistant to prompt phrasing and tone
Models screening & ranking logic
Designed for evaluation, not generation
FitToHire is purpose-built for resume evaluation
Not adapted from general language models or keyword heuristics. Engineered to understand what hiring systems miss — and show you how to fix it.