CVFAST is an AI resume builder for recruiters, staffing agencies, executive search firms, and hiring teams. It converts messy candidate resumes into consistent, branded, and ATS-compatible profiles for client submissions.
The platform addresses the time spent on manual formatting, inconsistent layouts, and administrative tasks. Users upload a candidate resume as a PDF, Word document, or profile from sourcing workflows. They then select from professional templates, apply agency branding that includes logos, headers, and preferred styles, and anonymize names, contact details, photos, or other sensitive information. An AI writer accepts plain English instructions to revise content, while the system can generate concise candidate summaries that highlight strengths, experience, and fit. The output remains fully editable so recruiters retain control before export.
Additional capabilities include PDF export of clean, structured documents with consistent headings and formatting that supports ATS compatibility. An optional Chrome extension allows importing profiles directly from LinkedIn, ATS pages, or other sources. Custom reusable templates are available for agencies with unique formatting requirements. The service emphasizes privacy and security through workflows designed with GDPR, CCPA, and PDPA considerations in mind.
It is delivered as a web-based platform with an optional browser extension. A free option exists to start, and paid plans can be canceled at any time with access continuing through the end of the current billing period. The product is developed by primehammer and made in Europe.
CVFAST sits in PulseGate's HR & recruiting category. It eliminates manual resume formatting and speeds up the creation of professional, branded candidate profiles for recruiters. CVFAST is a B2B product aimed at recruiters and staffing agencies. A free plan is available; paid tiers begin at $19. It runs on the web.
CVFAST first shipped in 2024. Among its 7 catalogued features are resume formatting, AI anonymization, and template selection.
Summary written by a language model from the project’s public pages.
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