Dazzle. Design readiness platform.
Benchmarks a designer's portfolio, case studies and resume, then scores how ready they are to get hired, with a plan to close the gap.
- Client
- Own product · FANG
- Year
- 2026
- Timeline
- 9 weeks to launch · live 7 months
- Role
- Product strategy, Brand & UI, Full-stack build
- Stack
- Next.js · Postgres · Claude API · Stripe · Vercel
Designers don't know why they're not getting hired
Portfolios get rejected silently. Dazzle's founders wanted a product that reads a designer's work the way a hiring manager does, and tells them, in one number and a short list, what to fix first. The hard part was making an AI judgement feel fair, specific and worth paying for.
- Problem
- No feedback loop between applying and rejection
- Bet
- A readiness score designers trust more than a friend's opinion
- Constraint
- Launch before the autumn hiring window
What we built.
Readiness score
One number from 0–100 with a confidence ring, built from weighted benchmarks across portfolio, case studies, resume and LinkedIn.
Benchmark engine
Structured rubric per asset, run through Claude with retrieval over our own dataset of hired-vs-rejected portfolios.
Fix-first plan
Each weak benchmark expands into a prioritised checklist and before/after examples, re-scored on every upload.
Brand & site
Warm, editorial identity that sits apart from the dark dashboards designers already ignore.
