Case Study
CVBORG – AI resume coach for humans
Shaped CVBORG into an AI resume builder that guides applicants and lets HR teams review structured context in one glance.
Overview
CVBORG started as a text box over GPT. I designed a multi-step onboarding, contextual edit states, and an org dashboard so candidates and recruiters speak the same visual language.
Problem / Goal
- Applicants pasted entire job descriptions, overwhelming the AI model.
- Recruiters wanted transparency around prompts and editing history.
- Pricing page did not reflect enterprise needs or compliance assurances.
My Role
Discovery interviews, UX flows, design system creation, and collaboration with the ML team on prompt guardrails.
Constraints
Needed to keep the stack React + Tailwind with minimal dependencies and ensure the AI requests stayed under token limits for free tiers.
Process
- Wireframe → broke onboarding into three micro-surveys that capture intent, target roles, and tone preferences.
- UI → built a layered card system that highlights AI suggestions versus user edits.
- Shipping → delivered component specs, tone sliders, and compliance-ready PDF exports.
Outcomes
- Applicants reach their first tailored draft 45% faster.
- Enterprise demo win-rate increased after shipping the compliance summary page.
- TODO: add metrics post-Series A.
Live Product
Next Steps
Hooking CVBORG into ATS partners and adding a portfolio builder for designers. Curious how this AI + human workflow could serve your team? See the beta or book a working session.