UTILITYAI PLATFORM

Purpose-Built for Utilities.
Deployed in Your Cloud.

You’ve invested in Snowflake, Databricks, copilots, and the cloud. None of them can decode a smart meter. UtilityAI deploys inside your environment to turn existing AMI data into actionable intelligence — giving your teams the visibility and tools they need to act on what’s really happening across the grid and behind the meter.

See the Platform

HOW IT WORKS

From raw meter data to decisions your teams can act on

Data Inputs

AMI / Smart Meter Data

CIS Customer Data

Grid & Feeder Data

EV Telematics

DER / Solar Data

Bidgely UtilityAI

Patented · 13 Years · Built for Utilities

Appliance-Level Disaggregation

EV Detection & Disaggregation

Load Forecasting & Dynamic Modeling

GenAI Energy Assistant

Purchase Propensity Models

Agentic AI Workflows

Deploy on your preferred cloud

cloud On Premise

Outcomes

Customer Engagement & HERs

EV Programs & Managed Charging

Grid Planning & DER Management

Energy Efficiency Programs

Analytics Workbench

PLATFORM ARCHITECTURE

The Vertical AI Intelligence Layer for Utilities.

Models run inside your environment. Your data never leaves. Deploy from the marketplace on any major cloud or data platform.

GenAI Fabric

Connects any LLM in your environment to the utility intelligence your meters already generate. One MCP server. Every LLM your organization already uses.

MCP Server

Exposes your utility models and data to any LLM in your environment
LLM Connectors

Microsoft Copilot, Claude, ChatGPT, and Glean

Explore the GenAI Fabric ↗

Agentic Automation Fabric

Production-ready agents for the workflows your teams run every day, and the infrastructure to build any agent your utility needs.

Prebuilt Agents

Ready-to-deploy for high bill analysis, transformer monitoring, and more
Custom Agents

Build unlimited agents tailored to your utility workflows

Explore Agentic Automation

25 Patents

90%+ EV Detection Accuracy

50M+ Meters

1TB+ AMI Data Daily

Built for Your Environment, Not Ours.

Your cloud, your data

Install from the AWS, Azure, or GCP marketplace. Your data stays inside your environment. Your security policies, your governance controls, your infrastructure intact from the moment you deploy.

Utility models, not general AI

Pre-trained on AMI data from utilities. Not a general-purpose model fine-tuned on a sample. That distinction matters when your CIO asks why the outputs are accurate enough to act on.

Agent-ready across the organization

The MCP server is included. Connect any LLM, build unlimited custom agents, and integrate directly with the CRM, DERMS, ADMS, and BI tools your teams already use. One deployment approval, every use case.

WHAT YOU CAN BUILD

From the meter to every
decision that matters.

Every use case runs on the same pre-trained models, the same data, and the same deployment your CIO already approved.

For Customer Experience, Call Center, and DSM

IVR personalization with appliance-level context
High bill complaint analysis agent
Marketing campaign tool integration
Custom DSM BI reports
Usage insights surfaced in your CRM
Customer-facing chatbots

For Grid Planning, Asset Management, and Operations

Transformer loading monitoring agent
DER load forecasting
Non-wires alternatives recommendation agent
Outage root cause analysis dashboard
Current-state DER analysis for interconnection requests
DERMS and ADMS integration

For Regulatory, Rates, and Internal Operations

Dynamic pricing simulation with appliance-level elasticity
IRP agent
Automated market potential studies
Cost and benefits analyzer for regulatory filings
Appliance-level inputs into system load forecasts
Rate analysis and design

Resources

Frequently asked questions

How can utilities use AMI data in their own cloud instead of moving it to a vendor environment?

Using AMI data in the utility’s own cloud starts with deploying the intelligence layer where the utility already runs its data, models, and governance controls. UtilityAI Pro runs inside the utility’s preferred cloud or on premises, turning smart meter data into customer, grid, and program intelligence without moving that data into a separate vendor environment.

Technology and analytics teams can activate meter intelligence while keeping infrastructure, security policies, and governance controls aligned to the environment their organization has already approved. Models run inside the utility’s environment, data stays there, and utilities can deploy from the marketplace on any major cloud or data platform.

How does UtilityAI Pro compare with general-purpose AI or cloud tools for utility use cases?

General-purpose AI and cloud tools can store data and run models, but they are not built to decode smart meter behavior or expose utility-specific intelligence on their own. UtilityAI Pro adds utility-trained models for appliance-level disaggregation, EV detection, dynamic modeling, propensity modeling, and agentic workflows as an intelligence layer purpose-built for customer, grid, and program use cases.

Enterprise teams can work from models trained on utility AMI data instead of adapting general-purpose AI that still needs to learn the structure of energy behavior before it becomes operationally useful. Bidgely backs this utility-trained foundation with 25 patents, 50M+ meters, 1TB+ of AMI data processed daily, and 90%+ EV detection accuracy.

How can utilities connect utility-specific intelligence to the copilots and LLMs they already use?

UtilityAI Pro connects utility-specific intelligence to the copilots and LLMs teams already use by integrating its MCP Server and APIs with tools such as Microsoft Copilot, Claude, ChatGPT, and Glean. Innovation, data, and business teams can bring meter-based context into these AI experiences without rebuilding the underlying AMI models each time a new interface is introduced.

A single MCP server exposes utility models and data to any LLM in the utility’s environment through connectors for Microsoft Copilot, Claude, ChatGPT, and Glean.

Can utilities build both prebuilt and custom AI agents on the same platform?

Building prebuilt and custom AI agents on the same platform means starting with ready-to-deploy workflows while retaining the flexibility to support utility-specific use cases over time. UtilityAI Pro includes prebuilt agents for workflows such as high bill analysis and transformer monitoring, along with an MCP-based foundation for utilities to build custom agents tailored to their customer, grid, and operational needs.

Teams can begin with an initial use case, then expand into additional workflows such as chatbots, trend monitoring, planning support, or internal copilots on the same approved platform. UtilityAI Pro includes production-ready agents, built-in MCP infrastructure, and support for unlimited custom agents within the same deployment.

How can utilities use one AI platform across customer, grid, and program teams?

Using one AI platform across customer, grid, and program teams starts with a shared utility intelligence layer that serves every business function. UtilityAI Pro uses AMI-driven models and a shared deployment to support customer engagement, EV programs, grid planning, DER management, energy efficiency, analytics workbench, rates, and internal operations from the same foundation.

Cross-functional teams can work from the same meter intelligence, data environment, and model layer while applying it to different workflows, from IVR personalization and high-bill complaint analysis to transformer monitoring, DER load forecasting, and regulatory analysis. One deployment approval covers every use case.

What data does UtilityAI Pro use?

UtilityAI Pro uses AMI or smart meter data as its core intelligence layer, then extends that foundation with other utility data when a use case requires additional context. Supported inputs include AMI or smart meter data, CIS customer data, and grid and feeder data, which feed the platform’s utility-trained models and workflows.

The shared data stack supports disaggregation, forecasting, targeting, agent workflows, and cross-team utility intelligence. Because model outputs live in the utility’s own data environment, utilities can combine them with other internal datasets, including outage, regulatory, and other sets of operational data, to support customer, grid, and program workflows.

How is UtilityAI Pro proven in utility operations?

Bidgely’s UtilityAI Pro approach applies utility-trained AI to real utility workflows, supporting scaled deployment across customer engagement, grid planning, and program operations from one shared intelligence layer. Results from Bidgely include 90%+ EV detection accuracy, support for 50M+ meters, and 1TB+ of AMI data processed daily, showing the platform’s scale and utility-specific intelligence foundation.

More details can be found within the following resources: the UtilityAI Pro page, the UtilityAI Platform Whitepaper, and the APS UtilityAI Pro customer snapshot.

Purpose-Built for Utilities. Deployed in Your Cloud.