Energy-theft & loss detection
Machine-learning models that flag anomalous consumption and probable theft to target field inspections and reduce AT&C losses.
Machine learning applied to electricity distribution — protecting revenue, improving billing integrity, and turning smart-metering and AMI data into operational intelligence for utilities.
Distribution utilities sit on large volumes of consumption, billing and metering data. SERRAO Analytics builds the models and pipelines that turn that data into revenue protection and operational decisions.
Our work in the sector spans revenue protection, tariff intelligence, smart-metering analytics and the cloud data engineering underneath — delivered with attention to the governance and residency constraints that public utilities operate under.
Machine-learning models that flag anomalous consumption and probable theft to target field inspections and reduce AT&C losses.
Detection of tariff-category misclassification and verification of preferential tariffs — including load-signature (NILM-based) checks.
Analytics on AMI and smart-meter data — consumption patterns, meter-data quality, and installation and adoption insight under RDSS.
Automated quality checks on meter readings and billing to catch errors before they reach the consumer.
Our AI-ML work in revenue protection was recognised by Gujarat Urja Vikas Nigam Ltd. (GUVNL) — a state power utility serving over 20 million customers — as a winner of its ElectronVibe 2025 Innovation Challenge, for the problem statement of reducing losses and thefts using AI and machine learning, selected from 65+ competing companies.
Awarded to CPC Analytics (Spinoza Consulting LLP) · Vibrant Gujarat Regional Conference
Client names are withheld under confidentiality; details are representative of delivered and in-progress work.
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.