Proglint — Enterprise AI for Real-World Operations
Solution // Revenue Protection

Loss Prevention & Revenue Protection

Flag un-billed food prep, sweethearting, self-checkout shrink, and unauthorized cash till access in real time.

Proglint Loss Prevention correlates live video feeds with POS transaction logs, UPI payment reconciliations, and cash till activity.

The Problem

QSRs and retailers lose gross margin to un-billed order passes, UPI payment drop-offs, self-checkout ticket swapping, and till theft — activity that leaves no record in the systems built to catch loss.

The Operational Challenge

Manual security reviews only sample a fraction of the footage generated, so most shrink patterns go unreviewed unless a discrepancy is already flagged elsewhere.

Approach

How Proglint Works

  1. 01

    Cameras monitor prep counters, payment desk, and self-checkout zones.

  2. 02

    AI cross-references visual order passes with live POS bill generation and UPI payment webhooks.

  3. 03

    Un-billed order passes or till incursions trigger instant supervisor alerts and evidence clips.

Included

Core AI Capabilities

Bill Not Generated Detection
UPI Payment POS Sync
Self-Checkout Ticket Swap Auditor
Non-Business Intrusion Alert

End to End

Workflow

01

Detect Order Pass

Visual AI detects food or retail item passing counter plane.

02

Reconcile POS / UPI

Checks POS receipt log & UPI confirmation within a short reconciliation window.

03

Flag Discrepancy

Generates evidence snippet in Enterprise Command Center.

Outcome

Business Impact

Closes the gap between prep-counter activity and POS records
Converts passive footage into verifiable audit evidence
Shrinks investigation time from a footage search to a flagged case

ROI Framework

The Business Case

A qualitative framework for evaluating impact — no figures are invented; this is how to think about the case until deployment-specific numbers are measured.

Shrink & Revenue Leakage Exposure

"How much of our loss is currently invisible to us?"

Unrecorded voids, un-billed food prep, and self-checkout ticket swapping share a common trait: none of them leave a record in the systems built to catch loss. A POS system can't flag a transaction that never happened. Exposure exists whether or not it is measured — continuous correlation between visual activity and transaction records is what makes it visible and actionable instead of a line item nobody can explain.

  • POS-visual discrepancies are surfaced as they occur, not discovered during a reconciliation cycle.
  • Loss patterns that don't generate a system record become detectable for the first time.
  • Investigation starts from a specific flagged event instead of a general shrink number.

Speed of Incident Response

"How long does it take us to go from an incident happening to someone acting on it?"

Without evidence-linked alerts, investigating an incident means someone pulling footage, reviewing it manually, and cross-referencing it against whatever records exist — a process that can take days for something that took seconds to happen. When an alert already arrives paired with the relevant video clip and the matching POS or sensor record, that investigation collapses to a pre-packaged case instead of a search.

  • Alerts arrive with evidence attached, not as a prompt to go looking for it.
  • Investigation time shifts from a multi-day footage review to reviewing a flagged case.
  • Response can happen while the situation is still active, not after the fact.

Under the Hood

Technology & Integrations

NVIDIA DeepStream POS Scanner Terminal Webhooks UPI Payment API Sync

Explore Further

Where This Solution Applies

ZERO OBLIGATION ENTERPRISE AUDIT

DISCUSS YOUR LOSS PREVENTION & REVENUE PROTECTION REQUIREMENTS

Schedule a customized demonstration with our enterprise AI engineering team. Discover how Proglint deploys across 2,500+ locations with zero camera teardowns.

Compatible with Existing Cameras 100% GDPR Anonymized Edge or Cloud GPU, Camera Agnostic