Why It Matters
Recruiters spend seconds scanning resumes. Automated filters discard many before a human even looks. We bridge that gap with clarity, structure, keyword alignment, and AI‑assisted intelligence.
Structured Feedback
Targeted guidance on headings, bullet phrasing, metrics, and alignment to role expectations.
OCR + Parsing
Robust PDF text extraction with OCR fallback for scanned or image-based resumes.
Keyword Insight
Detects missing role-critical terminology and suggests additions without keyword stuffing.
Impact Emphasis
Highlights weak verbs and vague statements so you can replace them with quantifiable achievements.
Compatibility Score
Aggregated scoring model reflecting ATS readability, structure validity, and content strength.
Privacy First
We only store what’s needed for your analysis history—delete anytime.
Under the Hood
Built with modern, composable tooling for speed, reliability, and maintainability.
- React Router 7
- TypeScript
- Tailwind + Utility Tokens
- shadcn/ui primitives
- Appwrite Auth & DB
- Appwrite Storage
- Gemini Models
- pdf.js + OCR (Tesseract.js)
- Edge-friendly Parsing
- Progressive Enhancement
Our Mission
We want candidates to spend less energy guessing what “the algorithm” wants and more time telling authentic achievement stories. By fusing semantic analysis, structural validation, and ATS‑style parsing heuristics, we surface the signal—and reduce the noise.
This isn’t about writing your resume for you. It’s about augmenting your revision workflow with immediate, accountable insight.
How Analysis Works
- 1. We extract clean text from your PDF (with OCR fallback for scans).
- 2. The content is segmented into sections & bullet density patterns.
- 3. AI model scores structure, clarity, impact verbs, and keyword alignment.
- 4. We calculate an overall ATS compatibility score.
- 5. You receive prioritized recommendations and improvement deltas.