Read any resume
Drop in a PDF from any template or decade. Structured data comes out the other side — name, history, skills, achievements — without a manual form.
Case study · Product · Built with AI
PrimeResume.ai — an AI resume optimizer, shipped in weeks.
Our founder's own AI product. Blank repo to live beta in dramatically less time than a traditional build — proof of the exact boutique delivery model we run for clients.
- Role
- Full build · design → code → ship
- Timeline
- Weeks, not quarters
- Status
- Live · primeresume.ai
Outcomes at a glance
Weeks
Blank repo to live beta
1,000+
Early users on the platform
Multi-model
Best tool for each step of the AI pipeline
Pay-per-use
Commerce built in from day one
The product
Upload a resume. Paste a job posting. Get an unrejectable version back.
PrimeResume.ai reads the resume you already have, scores it against the role you're chasing, and rewrites the weak bullets in language that passes Applicant Tracking Systems — without inventing experience you don't have. Export to DOCX, PDF, or Google Docs. Pay for what you use.
Analysis complete
ATS score
92/ 100
From 54/100 before rewrite.
Keyword coverage
- TypeScript
- System design
- Distributed systems
- Kubernetes
- Observability
- GraphQL
Product in action
What it actually looks like. Three moments from the live flow.
Screenshots from PrimeResume.ai itself — rendered in the product's own visual system, embedded here so this reads as a real case study, not an abstraction.
Step 1 · Intake
Paste the job description
The flow starts with the posting, not the resume — so every downstream suggestion is grounded in the role the candidate is actually chasing.
Step 2 · Analysis
Score, gap, suggestions
Named score, named keyword gap, named suggestions. This is the money shot — the moment a generic 'good resume' becomes a specific, fixable one.
Step 3 · Export
Download the rewritten resume
Rewritten bullets, updated scores, ATS-safe formatting, one-click download. The candidate leaves with a file, not a to-do list.
The problem
Over 90% of enterprise hiring runs through an ATS. Most resumes never reach a human.
Applicant Tracking Systems auto-rank candidates by keyword density, section structure, and formatting conventions. The good resumes that don't match the posting get filtered out before a recruiter scrolls past the first screen.
The fix — rewriting each resume for each role — is tedious enough that most candidates don't do it. And the generic AI writers that promise to do it for them invent experience candidates don't have, which shows up in the interview and ends the conversation.
90%+ of enterprise hiring flows through Workday, Greenhouse, Lever, Taleo, iCIMS — pick a keyword gap, get filtered.
Manual tailoring takes 30–60 minutes per role; most candidates apply to dozens.
Generic AI rewriters fabricate skills; a recruiter spots it the moment they ask a follow-up question.
What we shipped
Six capabilities, one end-to-end product.
None of these shipped as a demo. Each is live, paying, and serving real candidates today.
Score against the listing
Paste a job posting and see the ATS match score, the keywords you already have, and the exact ones you're missing for that role.
Rewrite for recruiters
Bullet-by-bullet rewrites grounded in the candidate's real experience — no fabricated roles, no invented skills, no tells.
Export anywhere
DOCX for Word and Google Docs, PDF for portals, editable source for final polish. ATS-safe formatting by default.
Pay-per-use commerce
Credit bundles from $4. No subscription, no expiry, no lock-in. Bought through a live checkout the day the product launched.
A resume library
Auth, cloud storage, and a history of every version the user has generated — so a candidate targeting ten roles keeps ten tailored resumes in one place.
How we shipped it
AI-native from the first commit. Boutique delivery, dramatic compression.
PrimeResume.ai is the clearest demonstration we have of the delivery model IB Digital runs for clients. Pair-programmed with Claude Code as primary IDE. Supported by Cursor where a different tool fit the task. Playwright test coverage authored by the same agents that wrote the features.
At runtime, the AI pipeline itself is multi-model: the right specialized model for parsing, for keyword analysis, and for content generation — routed through a single unified layer so the product can pick the best tool without a rewrite.
01
Pair-programmed with Claude Code
The same AI-native workflow we bring to every engagement. Principal engineer driving, Claude Code translating intent to diffs, humans owning the call on every architectural choice.
02
AI-authored test coverage
Playwright specs generated alongside the features they exercise. Regressions caught before every release, not discovered by users a week later.
03
Multi-model AI runtime
Specialized models for parsing, analysis, and generation — picked per step, swapped without touching the app. The same routing discipline we deploy on client builds.
The outcome
Weeks to live. A thousand users later, still shipping.
The feature set that would take a traditional team a full quarter — parse, score, rewrite, export, bill, and host — shipped, paid, and serving a thousand users inside a handful of weeks. PrimeResume.ai isn't a side project; it's the proof that the IB Digital delivery model works.
Let’s talk
30 minutes. Bring one problem.
No slide deck, no discovery call fee, no ‘request a quote’ games. We’ll tell you whether it’s a fit in the first call — and point you somewhere useful if it isn’t.