ATS Scanner
Paste your resume below. The scanner checks it against the parsing logic of the six biggest ATS systems and shows you exactly what gets extracted, what gets mangled, and what gets dropped entirely.
Paste your resume and hit Scan to see how this ATS reads it
Every ATS extracts your resume differently. A bullet that reads perfectly in Greenhouse might get swallowed by Workday. Dilly scans all six so you know where the gaps are before a recruiter sees a broken profile.
Greenhouse
~30% of tech internships
Strong structured parser. Handles standard formats well. Trips on tables, columns, and graphics. Skills extraction requires keyword density.
Lever
~18% of startup roles
Good at free-form text. Struggles with unusual date formats and multi-column layouts. Strong at pulling LinkedIn-style summaries.
Workday
~25% of enterprise roles
Notoriously strict. Drops anything it can’t categorize. Requires consistent section headers. Education parsing is particularly fragile.
iCIMS
~12% of finance roles
Aggressive skills matching against job description keywords. Low tolerance for non-standard formatting. Bullets must be clearly delimited.
Taleo
~20% of large enterprise
Oldest and least forgiving. Requires rigid section headers. Dates must be explicit MM/YYYY. Summary sections often dropped entirely.
Ashby
~8% of high-growth startups
Modern, flexible parser. Best at handling varied formats. Weakest at skills inference, must be explicitly listed to be counted.
Dilly scans all six systems and tells you exactly how to fix every failure before you submit.
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