Bidgely is an AI-powered SaaS company accelerating a clean energy future by enabling energy companies and consumers to make data-driven energy-related decisions. In this exclusive interaction with T&D India, Gautam Aggarwal, Chief Revenue Officer at Bidgely, explains why data is the new oil, and how Bidgely through UtilityAI™ Platform helps transform raw data into operational intelligence. Bidgely’s aim is to help utilities move closer to their goal of moving from from reactive operations to intelligent, predictive decision-making, notes Agggarwal. An interaction by Venugopal Pillai.
We broadly understand that Bidgely provides AI-power services to help energy producers take decisions, based on intelligently analyzed data. Tell us more.
Bidgely, a global Energy AI SaaS leader delivering AI/ML powered energy intelligence, turns smart meter data into clear, actionable insights for utilities. Indian discoms or global utilities can provide smart meter data — at 5-minutes, 15-30-60 minutes intervals — and then leveraging AI and machine learning, Bidgely enables energy providers with personalized insights and understanding on what’s happening on their grid, in their energy efficiency operations and inside customer homes—without installing any new hardware.
In simple terms, our technology helps utilities:
Reduce losses and protect revenue: By spotting anomalies, potential theft and unusual consumption patterns early.
Run a smarter, more predictable grid: Through feeder-level forecasting,peak-load visibility and predictive alerts that help operators prevent issues before they become problems.
Improve customer experience: With appliance-level insights, clearer bills and personalized recommendations that make energy use easier for consumers to understand and manage.
At its core, Bidgely brings clarity to the entire energy ecosystem—helping utilities operate more efficiently and deliver a better experience to the people they serve.
Utilities and energy providers, in general, have been investing in creating data infrastructure. What is the ultimate goal that these utilities seek to achieve with this data?
Data is the new oil. For most utilities, the core goal is to move from reactive operations to intelligent, predictive decision-making. As grids become more complex, data becomes the backbone for improving reliability, reducing losses and delivering a better customer experience.
Bidgely’s AI/ML platform plays a key role in this transition by helping Indian discoms turn raw meter data into real operational intelligence. With AI-driven personalized insights for energy efficiency, customer engagement, load shaping and demand forecasting, anomaly detection, billing clarity and appliance-level insights, utilities can:
- Shift from reactive problem-solving to predictive grid management
- Reduce non-technical losses through early detection of irregularities
- Improve billing transparency and customer trust
- Better plan for peak demand and load patterns
In essence, the ultimate goal is simple: use data to build a smarter, more efficient and more customer-centric grid—and AI is what makes that possible at scale.
Also, while data collection is one aspect, are utilities generally equipped to analyze this data to arrive at actionable decisions?
This creates a clear gap between collecting data and using data for real-time, high-impact decision-making.
Bidgely’s AI/ML platform helps bridge that gap by automating complex analysis, generating appliance-level intelligence, detecting anomalies early and delivering clear, actionable insights directly to utility teams. This enables discoms to move faster, make more informed decisions and unlock the full value of their smart meter investments without needing large internal data-science teams. With their patented, highly accurate AI/ML load prediction technology delivering ROI across customers, call centers and grid for 50M+ smart meters globally, Bidgely has now introduced GenAI capabilities on the same platform to deliver instant value and outcomes to customers and data analysts at discoms without sifting through multiple reports, dashboards and templates.
While data analytics has been around for some time, how has the advent of AI altered the dynamics?
Traditional analytics helped utilities observe trends; AI is enabling them to predict, classify and act with far greater accuracy and speed. The shift is transformational.
AI has made it possible to extract intelligence at a much deeper granularity—moving from periodic, high-level reporting to real-time, appliance-level insights that directly influence grid operations. It has also dramatically reduced the cost and complexity of running advanced use cases that were previously impractical or resource-intensive.
Bidgely, a global leader in AI-powered smart meter analytics, is helping utilities bridge this gap at scale. Through its patented UtilityAI™ platform, Bidgely converts raw smart meter data into actionable intelligence—making it possible to detect energy theft, reduce technical and non-technical losses, forecast feeder-level demand and empower consumers with personalized insights. In essence, AI has expanded what is possible and made these capabilities both operationally feasible and economically accessible for utilities.
Bidgely continues to deliver AI innovation at its best – with AI/ML powered patented foundation to GenAI capabilities to deliver NLP at your fingertips to Agentic workflows which will integrate into your horizontal AI tools such as Microsoft Co-Pilot, AWS Catalyst or ChatGPT.
“The transformation is being accelerated by real-world pressures: rising renewable integration, growing EV adoption and the need to better engage and empower customers.”
Is there any estimate on the extent to which power distribution utilities worldwide are currently “data-ready” or let us say, on a progressive journey towards digital transformation?
Globally, utilities are at very different stages of data maturity, but the direction is uniform: a rapid shift toward digital, data-driven operations. Most utilities today are somewhere in the mid-journey—having invested in smart meters, sensors and data platforms, but still building the capability to turn that data into operational intelligence.
The transformation is being accelerated by real-world pressures: rising renewable integration, growing EV adoption and the need to better engage and empower customers. These shifts demand far more visibility, forecasting accuracy and load management intelligence than traditional systems can provide.
This is where AI becomes a critical enabler. Platforms like Bidgely’s UtilityAI™ help utilities move from simply collecting data to actually using it—predicting load patterns, managing congestion, integrating distributed energy resources and offering consumers personalized, transparent energy insights. As utilities advance on this journey, AI is becoming the backbone of modern grid planning and operations.
Assuming that Bidgely helps in AI-driven data analytics, how do you deal with the different formats in which utilities have possibly collected and stored their data?
UtilityAI Pro™, designed as a security-first architecture by Bidgely, brings the capability to empower your cloud (AWS, Azure, OCI) or hyperscaler (Snowflake, Databricks) holding on to your GOLD – energy data i.e. smart meter data, CIS data, grid mapping data, billing and payment Data.
Imagine the world where Bidgely is sitting on top of your digital infrastructure to provide personalized and enriched insights to your business groups across customers, energy efficiency, call center and grid.
This flexibility allows utilities to adopt advanced energy intelligence and AI/ML analytics based on their cloud, hyperscaler or traditional MDM infrastructure, making AI deployment faster, smoother and far more cost-effective.
Currently, who are your major clients in the power distribution space?
Bidgely works with 45+ utilities globally, analysing data from more than 50 million smart meters across the US, Europe, the Middle East and India. Our partners include leading utilities such as NV Energy in Nevada (US), DEWA in the UAE and multiple discoms across India including Madhya Pradesh, Bihar, Uttar Pradesh and Gujarat. These collaborations span a wide range of use cases—from loss reduction and grid intelligence to customer engagement and energy efficiency.
“In our experience, both public and private utilities see strong value in AI-driven analytics—though their priorities may differ.”
Much of India’s power distribution is still in the hands of state government-owned discoms that might not be in the best of financial health and therefore a little “reluctant” to subscribe to sophisticated solutions. How do you read the situation? Do you therefore foresee more acceptance from private sector utilities?
In our experience, both public and private utilities see strong value in AI-driven analytics—though their priorities may differ. Many state-owned discoms are under pressure to reduce losses, improve billing efficiency and strengthen grid reliability, which makes solutions like energy theft detection, anomaly alerts and feeder-level forecasting highly relevant and cost-effective for them. At the same time, private utilities often focus more on peak-load management, customer experience and operational optimisation.
Bidgely’s platform supports both sets of needs. Because our solutions deliver measurable outcomes—loss reduction, improved collections, better grid planning and more informed customer engagement—we are seeing growing acceptance across the board.
Today’s power grid is getting complex for a host of factors including increasing RE injection. What complexities do you foresee in the years to come and how do you see the increasing relevance of Bidgely’s solutions?
Grid complexity will intensify as renewable energy injection grows, DERs proliferate, EV adoption accelerates and utilities push toward aggressive decarbonization goals. These shifts create more variability on the grid, increase peak-load stress and demand far greater visibility and forecasting accuracy than traditional systems can provide.
Bidgely’s AI-driven grid intelligence helps utilities stay ahead of this complexity—by predicting demand, managing DER and EV impacts, identifying losses early and supporting more efficient, decarbonized grid operations. This makes utilities better equipped to deliver reliability, reduce costs and meet long-term sustainability targets.