— Agent · for the COO · Owner

Void Hunter.

One name above the peer band.

Voids vs each store's own peer median, by store and by name. The pattern, not the verdict — the next step is a 5-minute review of the names flagged.

— What it catches

The signals.

  • Voids vs each store's own peer median (not industry benchmark)
  • Per-store + per-name void rate, flagged if > 1.5× peer median
  • Annualized excess-vs-peer dollar amount
  • Pattern detection — not verdict

— Data it needs

The input.

Employee performance CSV (Toast / Square / Clover / PDQ) with Location, Employee, Net Sales, Void Amount columns. Or a live POS connection.

— What you'll see

The output.

KPI strip · per-store table sorted by void rate · top-15 names sorted by void $.

— Sample signal

Mall Drive @ 3.36% void rate · 2.4× peer median · $14,840 annualized excess.

— POS support

Works with your stack.

Toast · Square · Clover · PDQ (CSV today) · Toast OAuth in approval

Don't see your POS? Drop a CSV at /trial — the parser auto-detects most column shapes. Or join the integration waitlist and we'll email you the moment the OAuth ships.

— Try Void Hunter on your data

60 minutes. Your real numbers.