HireScreen
Live at hirescreen.appAI resume scoring engine that processes up to 500 untrusted resumes and outputs a ranked shortlist with per-requirement reasoning. $299 per posting, no subscription.
From job posting to ranked shortlist
Paste requirements, drop resumes, get a ranked list with scores and reasoning. No setup. No subscription.
Unqualified candidates get a lightweight assessment. Qualified candidates get full detailed scoring with strengths, weaknesses, and per-requirement scores. The split reduces token usage by roughly 60%.
Resumes are untrusted input. Regex pre-flight scanning flags suspicious patterns before content reaches the model. XML delimiters isolate resume text, and the system prompt enforces data-only treatment.
$299 per posting matches how small businesses actually hire (2-3x/year). They resent recurring costs for intermittent needs. ~99% gross margin ($299 revenue vs ~$2 AI cost per batch).
One-time cost, no subscription. ~99% gross margin — $299 revenue vs ~$2 AI cost per batch of up to 500 resumes
Batch evaluation scores up to 500 candidates per posting. Prompt caching and two-tier output keep per-batch AI cost around $2.
Auth, Stripe payments, E2E tests (Playwright), data retention policies, and automated cold email outreach
Designing the scoring engine
The scoring engine is where the design work lives. Two-tier evaluation and token optimization determine how 500 untrusted resumes become a ranked shortlist.
no signal, no ranking
strengths, and per-requirement evidence
Three screens, one workflow
The whole point is getting a hiring manager from "I have 500 resumes" to "here are my top 10" without making them think about how.
Structured input so scoring is consistent The manager pastes a job description and the system pulls out requirements: must-haves vs. nice-to-haves, weighted by importance. That structure is the reason per-requirement scoring works at all. Without it, the AI scores holistically and you can't see why someone ranked where they did.
Scannable ranking, detail on demand This table answers one question: who's worth talking to? Candidates are sorted by score with bars for quick comparison. Click a row to see per-requirement breakdowns, strengths, weaknesses, and the AI's actual reasoning. Managers can check the work before scheduling anyone.
Per-requirement evidence and reasoning Every score shows its work. The detail view breaks the composite into per-requirement scores with confidence levels and plain-language reasoning. Strengths and weaknesses are separate so managers can weigh them. The number is a starting point, not the final answer.