AI & Machine Learning Deployments for Industry
Case Studies

Deployed across safety, power and custom builds

A selection of SERRAO Analytics deployments across our three practice areas. Client names are withheld under confidentiality; details are representative of delivered and in-progress work.

Real-time PPE compliance at a steel factory
Steel & Metals · Safety Monitoring

Real-time PPE compliance at a steel factory

Client
Confidential
Problem
Manual PPE checks could not cover the full floor across shifts, and violations went unrecorded.
Solution
Computer vision on existing CCTV detected helmet and jacket violations in real time, emailing supervisors a snapshot per event.
~98%Helmet-detection accuracy
~87%Violations caught in pilot
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Loading & unloading safety at a steel plant
Steel & Metals · Safety Monitoring

Loading & unloading safety at a steel plant

Client
Confidential
Problem
Material handling created unsafe proximity to trucks and inconsistent use of safety gear.
Solution
The system detects proximity to trucks during active operations and flags missing safety gear during loading and unloading.
ProximityAlerts near vehicles
GearChecks during handling
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Energy-theft detection for a state DISCOM
Distribution Utility · Power & Electricity

Energy-theft detection for a state DISCOM

Client
Confidential
Problem
High AT&C losses with limited ability to target field inspections effectively.
Solution
An anomaly-detection layer over consumption and metering data prioritised probable-theft cases for field verification.
AT&CLoss-reduction focus
TargetedInspection lists
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Tariff intelligence & revenue protection
Metropolitan DISCOM · Power & Electricity

Tariff intelligence & revenue protection

Client
Confidential
Problem
Revenue leakage from tariff-category misclassification and unverified preferential tariffs.
Solution
AMI-data models detect misclassification and verify preferential tariffs using load signatures (NILM).
AMIData-driven detection
NILMLoad-signature checks
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Fraud detection and risk management for a state power distribution utility
Public Sector · Power & Electricity

Fraud detection & risk management for a state DISCOM

Client
Confidential · Tamil Nadu power distribution utility
Problem
Revenue leakage across LT service connections, with billing and consumption data too large in scale for manual review — spanning roughly 3.3 crore LT consumers from 2021 onwards.
Solution
Data models built to analyse LT billing and consumption data at scale, generating exception (red-flag) reports that surface probable revenue leakage for targeted follow-up.
3.3crLT consumers analysed
Red-flagException reporting
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Discuss an AI-ML deployment

Tell us about your operation and we'll scope what machine learning can deliver — in safety, in the power sector, or as a custom build.