Polaris Grids Demonstrates How Artificial Intelligence Is Reducing Energy Losses and Transforming Power Distribution Across India

INDIA, September 2026

India's power distribution sector has a problem that costs billions of rupees every year. Electricity flows into distribution networks, passes through transformers, travels across thousands of kilometres of wire, and some of it simply disappears before it reaches a paying consumer. Some of this is technical loss, an unavoidable consequence of physics. A significant portion, however, is commercial loss: unbilled consumption, meter tampering, direct theft, and billing errors that accumulate across millions of accounts.

The national average for Aggregate Technical and Commercial losses, or AT&C losses, has historically sat between 20 and 25 percent. In some distribution circles, it is considerably higher. The electricity being lost is not a rounding error. It represents revenue that distribution companies cannot recover, operational deficits that affect infrastructure investment, and a burden that ultimately falls on paying consumers through higher tariffs.

Artificial intelligence, deployed through Advanced Metering Infrastructure, is changing how utilities approach this problem.

The Role of AI in Modern Meter Management

A conventional electricity meter records how much power has been consumed. A smart meter does the same thing, but at intervals as short as 15 minutes, and transmits that data automatically rather than waiting for a monthly field reading. When AI analytics platforms are connected to the data these meters generate, the system becomes significantly more capable than the sum of its parts.

The most immediate application is loss detection. When an AI model continuously compares the electricity injected at a distribution transformer against the sum of what all downstream meters are recording, discrepancies become visible in near real time. Patterns in that data tell an experienced analytics system something that no manual audit could detect at scale: whether the loss is random variation, equipment inefficiency, or a structured pattern consistent with tampering or direct hooking.

Outage management improves for similar reasons. A smart meter that stops communicating sends a signal. If multiple meters across a concentrated area go offline simultaneously, the system can map the affected zone immediately, dispatch field teams with accurate location data, and begin the restoration process before a single customer call has been logged.

Demand forecasting also shifts from a monthly estimate exercise to a continuous, data-driven process. AI models trained on historical consumption patterns, weather data, and real-time meter readings can generate forecasts that distribution companies use to manage load, plan maintenance windows, and avoid supply shortfalls during peak periods.

Polaris Grids: Building the Data Infrastructure Behind AI-Driven Distribution

Polaris Grids, formerly known as Gram Power and founded in California, operates as an Advanced Metering Infrastructure Service Provider across multiple Indian states. The company does not simply supply meters. It takes responsibility for the complete infrastructure stack: meter manufacturing and deployment, the communications network that carries data from meters to the cloud, and the analytics platforms that turn that data into operational decisions.

The company holds active AMISP contracts across Bihar through SBPDCL, Uttar Pradesh through MVVNL, Ladakh and Kargil through a 10-year REC contract, Manipur through MSPDCL, and West Bengal through WBSEDCL. Across these deployments, the smart meter manufacturer in India, like Polaris Grids manages the full lifecycle of metering infrastructure under long-term agreements with state distribution companies.

The AI capabilities embedded in the Polaris platform cover tamper detection at the individual meter level, feeder-level loss analytics, predictive alerts for meters at risk of communication failure, and consumption anomaly detection across consumer segments. These are not theoretical features. They are operational tools being used by distribution companies to prioritise field team deployments, reduce AT&C losses, and recover revenue that was previously invisible to them.

The Commercial Case for AI-Powered Metering

Utilities considering smart metering investments often frame the decision as a capital expenditure question. The infrastructure is real and the upfront costs are significant. What changes the calculation is the revenue recovery side of the ledger.
A distribution company reducing AT&C losses by even five percentage points across a large consumer base recovers a substantial sum annually. That recovery does not require new generation capacity or new transmission infrastructure. It requires accurate measurement, automated data collection, and analytics capable of identifying where the losses are occurring and flagging them for action.

The AMISP model, which Polaris Grids operates under, transfers the deployment and operational risk from the utility to the service provider. The distribution company pays for the service over the contract term rather than bearing the full capital cost upfront. The AMISP takes responsibility for meter availability, communication network uptime, and the accuracy of the data reaching the utility's systems.

This structure has accelerated smart meter deployment across India under the Revamped Distribution Sector Scheme, which targets 250 million smart meter installations nationwide. As of 2026, approximately 58 million meters have been installed, with the rollout continuing across all major distribution circles.

Looking Ahead

The next phase of AI application in smart metering is moving beyond detection and reporting toward prediction and automation. Models that identify meters likely to develop communication faults before they fail. Systems that detect gradual consumption decline patterns consistent with meter aging or calibration drift. Analytics that match grid load projections against real-time consumption to flag emerging imbalances before they become operational problems.

India's power distribution sector is in the middle of a transformation that has been discussed for more than two decades. The data infrastructure being built through smart meter deployment, and the AI capabilities being layered on top of it, are what finally make that transformation practical rather than aspirational.

For utilities, the question is no longer whether AI-powered smart metering delivers value. The evidence from deployments across Bihar, Uttar Pradesh, Ladakh, Manipur, and West Bengal makes that case clearly. The question is how quickly the remaining distribution circles can build the infrastructure to access the same capabilities.

About Polaris Grids

Polaris Grids, formerly Gram Power, is an Advanced Metering Infrastructure Service Provider operating across multiple Indian states. Founded in California and now headquartered in India, the company manufactures smart meters, deploys and manages communications infrastructure, and operates AI-powered analytics platforms for power distribution utilities. Active AMISP contracts cover Bihar, Uttar Pradesh, Ladakh, Manipur, and West Bengal. Polaris Grids is working toward universal electricity access through intelligent grid management.

Website: https://www.polarisgrids.com/