Bidgely Introduces UtilityAI Pro: Turning Utility Data into Strategic Insight
October 24, 2025 - Bidgely unveiled UtilityAI Pro, a vertical AI platform built specifically for utilities. It plugs into a utility's preferred data environment to analyse advanced metering infrastructure (AMI), customer, and grid data with 10x greater granularity. The result: behind-the-meter context on appliance-level consumption, customer behavior, and grid performance that strategy and operations teams can act on.
Bidgely brings more than a decade of utility-focused ML and AI expertise to the table, backed by 19 patents and billions of meter reads. The company processes over a terabyte of energy consumption data daily across global customers.
Why This Matters for Executive Teams
Electrification, data center growth, regulatory pressure, affordability concerns, and an ageing grid are redefining priorities. CIOs are investing heavily in data foundations, yet many still struggle to convert AMI and enterprise data into measurable value. One recent survey notes only 20% of utilities have completed digital transformation, while the vast majority see AI and analytics as essential.
UtilityAI Pro addresses that gap by making granular data usable across customer, grid, and enterprise functions-without forcing data out of the utility's trusted cloud.
What UtilityAI Pro Is
UtilityAI Pro is a unified platform of utility-specific ML models that runs in your existing cloud and data lake. It enriches your enterprise systems and AI copilots with appliance-level and feeder-level insight, so teams can move from raw data to decisions quickly.
"As the longtime leader in utility-specific AI technology, we hear consistently from CIOs their hesitation to share critical infrastructure data outside their established cloud. We developed UtilityAI Pro as a single platform with patented utility-specific machine learning models designed to power existing investments in data lakes, generative and agentic AI on the utility's cloud. This focus ensures technology leaders can drive transformation across the entire utility," said Abhay Gupta, CEO of Bidgely.
"By partnering with the top players in the cloud ecosystem, CIOs can deploy UtilityAI Pro on the cloud platform of their choice to drive change securely and at scale."
Hunter Horgan, managing director at Renown Capital Partners and Bidgely investor, adds: "This flexibility allows Bidgely to enrich all utility applications with granular, behind-the-meter intelligence, maximizing the ROI of existing data investments."
Deployment Model and Data Governance
UtilityAI Pro is deployed within the utility's chosen cloud, aligning with existing security, IAM, and compliance practices. It is built to interact with your data lake, your copilots, and your agents-minimising data movement and avoiding new silos.
For leaders standardising on AMI and grid-modernisation investments, that means deeper analytics with fewer integration headaches. For context on AMI, see the U.S. Department of Energy overview here.
Capabilities That Move the Needle
- Deep Customer Profiling: Granular, behind-the-meter views on appliance ownership, performance, and evolving usage behavior.
- AI-Powered Customer Engagement: Hyper-personalised communications, improved call center efficiency, and higher program enrollment.
- Precision Targeting: Identify ideal candidates for rates and programs using actual device ownership and reliable propensity modeling.
- Intelligent Grid Modernisation: Bottom-up predictive visibility to diagnose grid stress points and prioritise resiliency investments.
- DER Management: Forecast and manage the grid impact of solar, storage, and EVs to maintain system stability.
- Accelerated Innovation: Rapid prototyping and deployment of custom AI applications inside the utility's tech stack.
- Operational Excellence: Democratise real-time intelligence across customer, grid, and back-office functions to improve management and reduce costs.
Executive Use Cases and Expected Outcomes
- Rates and Programs: Target households by appliance ownership and usage shifts to improve TOU adoption, demand flexibility, and income-qualified program reach.
- Call Center and Digital CX: Give agents and bots appliance-level context to cut handle time and increase first-contact resolution.
- Grid Planning: Identify feeder stress from bottom-up load signatures to optimise capital plans and reduce overload incidents.
- DER Orchestration: Forecast EV charging, solar backfeed, and storage to balance hosting capacity and maintain reliability.
- Revenue and Affordability: Spot abnormal usage trends, support arrears management, and maintain service quality without increasing cost to serve.
Pragmatic Rollout for CIOs
- Phase 1 - Foundation: Integrate with your data lake and identity systems; validate appliance-level disaggregation on a representative AMI cohort.
- Phase 2 - First Wins: Launch one high-ROI pathway (e.g., rate targeting or call center assist) with clear KPIs and executive sponsors.
- Phase 3 - Scale: Extend to grid planning and DER forecasting; connect insights to copilots and agent workflows across the enterprise.
- Phase 4 - Industrialise: Establish MLOps, data quality SLAs, model monitoring, and cost governance with FinOps guardrails.
Metrics to Track
- Program enrollment lift and participation cost per acquisition
- CSAT/NPS, average handle time, and first-contact resolution
- Peak demand reduction and load shifting (kW, kWh)
- Feeder overload prediction accuracy and time-to-diagnosis
- DER forecast error (MAPE) for EVs, solar, and storage
- Time-to-insight from AMI read to operational decision
- Cloud cost per analytic and per customer served
Risks and How to Mitigate
- Data Quality: Establish automated checks for AMI gaps, clock drift, and device mappings; surface lineage to users.
- Model Drift: Implement continuous monitoring with retraining triggers tied to seasonal and DER penetration shifts.
- Privacy and Trust: Enforce data minimisation and differential aggregation for outreach use cases; align with the NIST AI RMF guidance.
- Change Management: Train agents, planners, and product owners on how to interpret appliance-level insights; define decision playbooks.
- Vendor Lock-In: Deploy in your cloud of choice with clear export paths and API standards to keep optionality.
The Bottom Line
UtilityAI Pro gives executives a way to turn AMI, customer, and grid data into precise decisions that cut costs, improve reliability, and strengthen customer outcomes. It fits into the utility's existing cloud and data program, so teams can move quickly without compromising governance.
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