Scores stay explainable
Career and job-fit scores are deterministic. AI extracts structure from messy text, but it does not decide the ranking.
PathFinder turns a student's resume, projects, assessments, and saved jobs into explainable fit scores, evidence-backed skill gaps, and a roadmap they can act on.
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Answer a short, structured questionnaire and get transparent, data-driven career matches.
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Upload a resume or enter your background, and get a phase-by-phase roadmap to become a top candidate.
Not an LLM ranking engine
The system separates uncertain extraction and feedback from the scoring, evidence, dependency, and scheduling logic a user should be able to inspect.
Career and job-fit scores are deterministic. AI extracts structure from messy text, but it does not decide the ranking.
Assessments, resume entries, and GitHub signals contribute different confidence levels instead of collapsing into a skill keyword list.
Dependencies, priorities, effort, and target dates are scheduled by deterministic domain logic with a usable no-AI fallback.
A few minutes of questions about your interests, comfort with math and hands-on work, and what you actually want out of a career.
A weighted, explainable match against real career data across fields, or a roadmap for the career you already have in mind.
Concrete academic priorities, portfolio projects, and interview preparation, sequenced so you know what to do next.