Blog
Practical writing on AI-assisted resume review with evidence — for small HR teams, not content farms.
2026-07-10
ReviewStack quota rules explained
When an analysis settles, when it releases, and how monthly grants differ from top-ups.
Read →2026-07-09
PDF and DOCX resume limits that affect AI screening quality
Searchable text, page caps, OCR for scans, and how file quality affects explainable scoring.
Read →2026-07-08
Why human review status still matters in AI screening
Scores are inputs. Human review states turn evidence-backed scores into an actionable hiring workflow.
Read →2026-07-07
AI resume screening is not an ATS replacement
Where ReviewStack fits relative to applicant tracking systems — and why we do not claim to be an ATS.
Read →2026-07-06
ReviewStack trial vs paid: what you get
Compare the free trial (10 analyses) with the $59/month plan and $19 top-ups — no seat fees.
Read →2026-07-05
Resume PII, redaction, and retention basics for screening tools
What ReviewStack retains, what gets redacted before model calls, and how long files stay available.
Read →2026-07-04
Designing a resume scoring rubric that hiring managers trust
Criteria, weights, and 0–4 anchors — how to make rubric-based, evidence-backed screening explainable.
Read →2026-07-03
Bulk resume screening for SMB hiring managers
A practical batch workflow for PDF/DOCX resumes when you need speed and evidence — without an enterprise ATS.
Read →2026-07-02
How to score resumes without auto-rejecting candidates
Decision-support scoring is not the same as automated rejection. A safer pattern for small hiring teams and solo recruiters.
Read →2026-07-01
Evidence-based resume screening for small HR teams
Why source quotes beat black-box scores when HR teams and solo recruiters screen resumes at volume.
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