Computer Vision

Deploying Surveillance AI at Scale

Client: National Manufacturing Consortium

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Executive Summary

The National Manufacturing Consortium (NMC), operating over 500 manufacturing units across India, faced a critical operational bottleneck: ensuring workplace safety and perimeter security at scale. Traditional manual monitoring was reactive, error-prone, and resource-heavy. QuillDB deployed a state-of-the-art Surveillance AI ecosystem, transforming their passive CCTV infrastructure into an active, intelligent safety shield.

The Challenge: Blind Spots at Scale

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    Safety Blind SpotsWith over 50,000 cameras, less than 1% of footage was reviewed, leaving safety violations unnoticed.
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    Latency IssuesCloud uploads caused 30-60s delays, rendering fire/intrusion alerts useless for real-time action.
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    Compliance GapsManual audit logs were incomplete, leading to regulatory fines and operational risks.
60s+
Old Alert Latency
< 1%
Footage Reviewed

Our Solution: Edge-First Intelligence

We re-architected the surveillance stack, moving intelligence from the cloud to the Edge for real-time inference.

Edge Compute

NVIDIA Jetson modules process video locally, cutting latency to <2s.

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Custom Vision

Models trained on client data for PPE, Fire, and Intrusion detection.

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Command Center

Unified HQ dashboard with heatmaps and automated compliance reports.