jdmatchr - Purpose-built AI for modern hiring workflows
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Streamline your hiring process with AI-powered resume screening. Upload resumes, paste job descriptions, get instant scores and detailed analysis!
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Maker
📌
🚀 Hi Product Hunt!
I’m super excited to share jdmatchr with you all today!
As someone who’s been around hiring teams, I kept seeing the same problem: manually screening resumes is slow, inconsistent, and often biased. Many ATS platforms are too complex for quick screening, and LLMs requires custom prompts that aren’t reliable or scalable.
So I built jdmatchr — a simple tool that lets you:
✅ Upload 1–50 resumes (PDF, JPG, DOCX, etc.)
✅ Paste a job description
✅ Instantly get ranked candidates with scores and skill match breakdowns
No prompts, no noise — just fast, AI-powered resume screening that actually helps you shortlist faster.
If you’re in HR, recruiting, or even hiring your first few employees — I’d love for you to try it out and tell me what you think!
Happy to answer any questions, and I’d be incredibly grateful for your feedback 🙏
The 1-50 resumes range is perfect. Most tools either force you to do one by one or expect you to have hundreds. That sweet spot for small to medium hiring rounds is exactly where the manual pain hits hardest.
Love that you're tackling the prompt engineering headache too. I've seen so many teams struggle with getting consistent results from generic LLM tools. Having reliable scoring builtin sounds like a game changer.
Quick question, does it handle different resume formats well? I've seen some really creative CVs that break traditional parsing. Either way, bookmarking this for our next hiring round!
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Maker
@kkant041 Thanks so much! 🙌 Really appreciate you noticing that sweet spot; we saw the same pain point across growing teams: too big for manual sorting, too small for enterprise ATS bloat.
And yes! jdmatchr is built to handle multiple formats — PDF, DOCX, JPG/PNG (for scanned resumes), and even some quirky layouts. We use a layered approach: file pre-processing → OCR fallback → AI-based parsing — so even “creative” resumes don’t break things (most of the time 😅).
Would love to hear how it works for your team when the time comes! And always open to edge case examples, they help us improve fast
Non-traditional resumes were actually one of the trickiest parts. We use a mix of layout analysis, OCR, and AI parsing to handle those odd formats. Not perfect yet, but solid for most cases.
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Congrats on the launch, @surya_kant4 !
The 1-50 resumes range is perfect. Most tools either force you to do one by one or expect you to have hundreds. That sweet spot for small to medium hiring rounds is exactly where the manual pain hits hardest.
Love that you're tackling the prompt engineering headache too. I've seen so many teams struggle with getting consistent results from generic LLM tools. Having reliable scoring builtin sounds like a game changer.
Quick question, does it handle different resume formats well? I've seen some really creative CVs that break traditional parsing. Either way, bookmarking this for our next hiring round!
@kkant041 Thanks so much! 🙌 Really appreciate you noticing that sweet spot; we saw the same pain point across growing teams: too big for manual sorting, too small for enterprise ATS bloat.
And yes! jdmatchr is built to handle multiple formats — PDF, DOCX, JPG/PNG (for scanned resumes), and even some quirky layouts. We use a layered approach: file pre-processing → OCR fallback → AI-based parsing — so even “creative” resumes don’t break things (most of the time 😅).
Would love to hear how it works for your team when the time comes! And always open to edge case examples, they help us improve fast
Congrats on the launch @surya_kant4!
This solves a real headache, fast, no-prompt resume screening is exactly what busy hiring teams need.
Clean UX + practical output = win.
Curious how it handles non-traditional resumes.
Great job! 🚀
@betterwithmk Thanks a ton, Mayank! 🙌
Non-traditional resumes were actually one of the trickiest parts. We use a mix of layout analysis, OCR, and AI parsing to handle those odd formats. Not perfect yet, but solid for most cases.
Really appreciate the kind words! 😊