One founder. Thirty tools. The whole job search.
The Problem I Set Out to Solve
Most job seekers lose before they start. They write a resume once, blast it to fifty openings, and hear nothing back. The reason isn't that they're unqualified — it's that applicant tracking systems (ATS) filter them out before a human ever reads the document. The average corporate role receives 250 applications. Roughly 75% are rejected by automated keyword matching before a recruiter opens the file.
I watched this happen to people I knew — experienced professionals, recent graduates, career changers — all getting ghosted by machines. The tools that existed to help were either overpriced, oversimplified, or actively harmful (fabricating credentials, inflating metrics, hallucinating experience). I wanted to build something that actually worked: an engine that restructures your real experience to match what the system is looking for, without inventing anything.
That's where TailorMeSwiftly started. It grew into something larger.
What I Built
TailorMeSwiftly does three things across the full job search:
Resume tailoring — ATS keyword optimization, recruiter heatmap simulation, cover letter automation, cold outreach drafting, and a brutal roast that tells you exactly where your resume fails. The AI never fabricates credentials. Everything is based on your actual resume, and you review it before use.
Skill building — Identifies gaps between your current abilities and your target roles, then builds personalized learning plans with spaced repetition. The goal is real competency, not certification cramming.
Industry briefings — AI-curated daily briefings and an auto-generated podcast. Show up to interviews knowing what happened in your industry yesterday, not what was in a textbook two years ago.
Thirty-plus tools total. Resume builder, interview prep with voice AI, salary negotiation scripts, ghosting predictor, toxic culture radar, referral mapper, rejection reverser, and more. A Chrome extension captures job postings from 12+ boards. Each tool addresses a specific failure point in the modern job search.
Beyond the consumer product, I built the institutional layer: an admin dashboard with WIOA-aligned reporting, a developer API with 11 documented endpoints, a Career Readiness Score that composites across all three products, and full compliance infrastructure — DPA templates, FERPA-conscious controls, SOC 2 alignment, and a Section 508 accessibility statement. Sixty-seven public pages, all with semantic HTML and ARIA landmarks.
Proof of Work
Technical Foundation
Vanilla JavaScript front-end — no framework lock-in, no dependency sprawl. Supabase back-end: PostgreSQL with Row-Level Security, Edge Functions, and real-time subscriptions. AI layer powered by Gemini with custom prompt engineering for each of the 30+ tools. Hosted on GitHub Pages.
Three deliberate architectural constraints: a zero-fabrication policy (the system never invents credentials), algorithmic transparency (users can see why outputs are structured the way they are), and privacy-by-design (data minimization, encrypted at rest, no third-party data sharing). The spaced repetition system implements the SM-2 algorithm. The recruiter heatmap is based on published eye-tracking research.
The architecture is deliberately simple because the complexity lives in the AI layer — semantic keyword weighting, recruiter heatmap simulation, adaptive assessment scheduling, and content curation algorithms. These are the hard problems. The infrastructure should get out of the way.
More detail on the R&D behind each engine is available on the Research & Development page.
Why This Matters
The hiring process is broken in a specific, measurable way: qualified people are being filtered out by systems they don't understand. This isn't a minor inefficiency. It affects career trajectories, economic mobility, and who gets access to opportunity.
First-generation college students, career changers, veterans transitioning to civilian work, refugees rebuilding professional lives in a new country — these are the people who get hurt most by opaque automated screening. They have the skills. They don't have the system literacy to get past the gate.
TailorMeSwiftly exists to fix that asymmetry. Not by gaming the system, but by making it transparent — showing people exactly what ATS software is looking for and restructuring their real experience to match. Career access is a lever for economic mobility. Professional-grade career preparation — the kind previously available only through expensive coaches or elite university career centers — should be accessible to anyone with an internet connection.
The AI in this platform augments human judgment rather than replacing it. It doesn't decide who is qualified. It ensures that qualified people aren't filtered out by systems they never learned to navigate. That's the difference between AI that concentrates advantage and AI that distributes it.
The Institutional Vision
The same tools that help an individual job seeker can serve 10,000 participants at a workforce nonprofit — with the compliance infrastructure already in place. TailorMeSwiftly is built for institutional licensing: workforce development organizations, community colleges, refugee resettlement agencies, and vocational rehabilitation programs.
The admin dashboard supports WIOA-aligned outcome reporting. The developer API integrates with existing case management systems. FERPA-conscious data controls and a DPA template are ready for procurement review. This isn't a consumer app trying to bolt on enterprise features — the institutional layer was designed from the start.