Upload a PDF, DOCX or TXT resume and TalentGraph returns contact details, skills, work history, education and projects as structured JSON — with skills normalized, tenure and seniority derived, and employment gaps flagged. A cached, self-learning local engine handles most fields; the AI model is called only to fill what it can't. Parsed resumes are added to your talent pool for Talent Match.
Try it now ↓Seen this exact resume text before? Return the structured result instantly — zero AI calls.
Regex, a learned skills gazetteer and learned section headings extract most fields with no API call.
Only when local confidence is below threshold does it call Gemini, OpenAI or Anthropic to fill the gaps.
Every AI answer teaches the local engine new skills and headings, so future resumes need the AI less.
The document is processed by the TalentGraph API running alongside this page. Nothing leaves the machine except the text the local engine can't resolve on its own.
Drag & drop a resume here
or
PDF, DOCX or TXT · max 10MB
Parsed results will appear here.
Watch the AI-call rate trend down as more resumes get processed.
Three properties that come from processing locally first.
The exact-match cache answers repeat documents instantly and the local rule engine handles most of the rest. A model call is the exception, not the round trip you wait on every time.
Every AI fallback teaches the local engine new skills and headings, so the share of documents needing a model call keeps falling. Your cost per document goes down as volume goes up.
Each result shows which path produced it — cache, local rules, or AI — so you always know how much of the output was inferred and how much was read.
The same JSON that powers matching and search — and that drops straight into your ATS.
PRIYA RAGHAVAN priya.r@example.com | +91 98200 11223 | Pune EXPERIENCE Senior Backend Engineer, Northwind Labs Mar 2021 - Present - Rebuilt billing service on Python/FastAPI - Cut p99 latency 840ms -> 120ms with Redis Backend Engineer, Cobalt Systems Jul 2018 - Feb 2021 EDUCATION B.E. Computer Science, COEP, 2018 SKILLS Python, FastAPI, PostgreSQL, Redis, Docker
{
"name": "Priya Raghavan",
"email": "priya.r@example.com",
"phone": "+91 98200 11223",
"location": "Pune",
"total_experience_years": 7.2,
"seniority": "senior",
"current_title": "Senior Backend Engineer",
"skills": ["Python", "FastAPI", "PostgreSQL",
"Redis", "Docker"],
"education": [
{ "degree": "B.E. Computer Science",
"institution": "COEP", "year": 2018 }
],
"employment_gaps": []
}Drop a file in and watch which path answers it.
1 Drop Rahul_Agarwal_resume.pdf onto the upload area 2 Text extracted (column-aware) 0.4s 3 Cache lookup .................. miss 4 Local rule engine ............. 31 of 34 fields, confidence 0.91 5 AI fallback ................... 3 fields filled 6 Result badge: AI · total 2.1s 7 Candidate added to talent pool — now matchable
The free tier needs no card. If you would rather see it on your real requisition load first, we will walk through it with you.