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CLUSTER EXTRACTS-JOB-RESUME · 4 ENTRIES · EARLIEST ENTRY 2026-09-03

Resume screening and matching apps

The cluster consists of resume screening tools that extract text from PDFs, compare candidates to job descriptions, and produce match scores and rankings. The cluster's dated history is too thin to read a shape from, as it predates the index or its members are undated. Among the members, ai-resume-screening-system, ResumeRA, and Number1CV lead on activity signal, though all currently show zero stars.

Entry timeline

ENTRY TIMELINE

SEP 2026: 2OCT 2026: 2
SEP 2026OCT 2026

Each bar is the month a member carries, which is a creation date where the source published one and a crawl date otherwise. Nothing in the index was found before 11 August 2026, and coverage broadened sharply on 14–15 August, so a bar from then on reports how much we found that month, not how much was built; an earlier bar reports how far back a member's own source dated it — not how long we have been watching.

Members by activity

Activity signals, not revenue.

Build origin · 4 unlabelled

Operator · 2 hobby · 2 unlabelled

Two labels per entry, never collapsed into one: how it was built, and who stands behind it. Counted over the 4 listed below. Unlabelled means nothing has decided yet — not that the answer is small.

  1. 01ai-resume-screening-system0★2 daysliveResume screening app that extracts text from PDFs, matches candidates to job descriptions, ranks them, and exports results.
  2. 02ResumeRA0★19 days—hobbyResume screening app that extracts text from PDF resumes, scores candidates against a job description, and presents a ranked table with explanations.
  3. 035-Day-Remote-AI-OS-Sprint0★1 mo—Candidate screening app that parses resumes and job specifications into evidence dossiers with cited matches and human sign-off before export.
  4. 04Number1CV0★1 molivehobbyResume screening app that extracts text from PDFs, compares candidate profiles to job descriptions, and calculates match scores with missing skills.

Ranked by traction, highest first, and paged 20 at a time — this is a window on the cluster, never the whole of it. Ties are broken by a stable id so a product cannot appear on two pages or fall between them. Browse every cluster.