Bidgely is positioning its behind-the-meter artificial intelligence to address critical operational inefficiencies within the ASEAN energy sector. The company will present its UtilityAI™ platform at Enlit Asia 2026, scheduled for 22–24 September in BSD City, Jakarta. By leveraging advanced machine learning and big-data analytics, Bidgely aims to help regional utilities convert existing Advanced Metering Infrastructure (AMI) data into actionable intelligence. This strategic move targets three specific enterprise pain points: revenue protection through theft detection, grid stability amidst rising distributed energy resources, and the mitigation of customer dissatisfaction caused by billing volatility.
Deploying UtilityAI for Revenue and Grid Intelligence
Bidgely intends to demonstrate how its AI/ML-based analytics can transform interval data into specific operational outcomes for Southeast Asian utilities. A primary focus involves revenue protection, where the company proposes using AMI anomaly algorithms to identify non-technical losses. Rather than relying on traditional, reactive audit routines, Bidgely suggests that these algorithms can provide high-accuracy leads to pinpoint energy theft. Additionally, the company is targeting grid intelligence to manage volatility from solar power and electric vehicles. By building bottom-up models of distribution assets, Bidgely claims utilities can gain visibility into transformer capacity and asset stress, potentially allowing them to defer capital expenditures (CAPEX) and optimize operating expenses (OPEX).
Flexible Deployment Across Enterprise Cloud Ecosystems
Recognizing the diverse data governance and security requirements of regional utilities, Bidgely is offering multiple deployment paths for its UtilityAI™ platform. The company states that the solution can be implemented as a fully managed Software-as-a-Service (SaaS) model or integrated directly into a utility's existing cloud and data environment. Supported ecosystems include Amazon Web Services (AWS), Microsoft Azure, Snowflake, and Databricks. This flexibility is designed to allow utilities to adopt AI capabilities while maintaining compliance with enterprise IT standards and leveraging current technology investments. The company's technical sessions at the event will specifically address managing AI implementation when working with fragmented or imperfect data systems.
Key Takeaways
- Bidgely will present its UtilityAI™ platform at Enlit Asia 2026 in Jakarta from 22–24 September.
- The platform aims to combat non-technical losses using AMI anomaly algorithms to identify energy theft.
- UtilityAI™ supports deployment via SaaS or within existing ecosystems like AWS, Microsoft Azure, Snowflake, and Databricks.
TechInsyte's Take
In our view, Bidgely’s focus on the ASEAN region highlights a critical shift from simple AMI deployment to sophisticated data monetization. While many utilities have invested heavily in smart meter hardware, the ability to extract granular, appliance-level insights remains a significant hurdle. By offering deployment flexibility across Snowflake and Databricks, Bidgely is directly addressing the "data silo" problem that often prevents enterprise AI adoption. This approach suggests that the next phase of grid modernization will not be defined by new hardware, but by the software layer's ability to turn massive, imperfect datasets into precise operational intelligence for managing DER-driven volatility.
Questions & Answers
How does Bidgely plan to address revenue protection for Southeast Asian utilities?
Bidgely proposes using advanced AMI anomaly algorithms to replace slow, reactive audit routines. These algorithms are intended to provide high-accuracy leads and evidence to help utilities pinpoint energy theft and reduce non-technical losses.
What technical deployment options are available for the UtilityAI™ platform?
The platform can be deployed as a fully managed SaaS solution or integrated into a utility's preferred cloud and data ecosystem, specifically including AWS, Microsoft Azure, Snowflake, and Databricks.
How can Bidgely's technology assist in managing grid volatility from solar and EVs?
The company aims to build bottom-up models of distribution assets. This is intended to provide visibility into transformer capacity, asset stress, and load-shifting potential, which may help utilities optimize OPEX and defer CAPEX.
What specific customer experience issue is Bidgely targeting?
Bidgely is targeting "bill shock," which it identifies as a leading cause of customer dissatisfaction. The company intends to use appliance-level usage insights to provide personalized data to consumers and actionable data to Customer Service Representatives.
Source: Businesswire
