An intelligent job hunting platform that scrapes LinkedIn, detects company tech stacks with 55+ algorithms, matches jobs to your skills using hybrid vector search, and generates tailored resumes—automatically.
From job discovery to tailored application—fully automated.
Playwright automation
55+ tier detection
Vector + BM25 hybrid
GAT-spec tailored
Pain-point targeted
What makes GraphCommand different from manual job hunting or basic job boards.
Not just "Company uses React." GraphCommand detects frameworks, versions, CDNs, analytics, CMS platforms, tech debt signals, hiring indicators—everything.
Pure vector search misses exact keywords. Pure keyword search misses semantics. GraphCommand combines both for 23% higher match accuracy.
Knowledge graph with PageRank prioritization. Multi-hop reasoning: "Spec A solves Problem B which relates to Skill C."
Progressive fallback for 100% coverage with optimal performance. Plain parsing first, full browser only when needed.
Not generic templates. Each cover letter addresses the company's specific challenges detected by the War Room analysis.
Interactive HTML reports with Mermaid diagrams. Tech stack visualization, pain points ranked by opportunity, ready-to-use pitch narratives.
TechStackXRay: 13,855 lines of detection algorithms organized into 5 major tiers.
What a generated company intelligence report looks like. Real output from analyzing a software consultancy.
Time and quality comparison for a typical job hunt workflow.
| Task | Manual Approach | GraphCommand |
|---|---|---|
| Research one company | 4-6 hours (Google, LinkedIn, blog reading) | 2 minutes (automated War Room) |
| Detect tech stack | 10-15 technologies (obvious ones) | 47+ technologies (55 detection tiers) |
| Match job to skills | Gut feeling, keyword scanning | Hybrid vector + BM25 (23% more accurate) |
| Tailor resume | 30-60 min per application | 5 seconds (GAT-spec auto-generation) |
| Write cover letter | Generic template, no research | Pain-point targeted, company-specific |
| Process 50 jobs | ~40 hours over 2 weeks | ~10 minutes fully automated |
A serious tech stack for a serious problem.