Building Energy Efficiency Programs with AI-Powered Analytics for a U.S. Based Construction Firm
Client Overview
Headquartered in the U.S., the client provides engineering, consulting, and construction management services across the energy, infrastructure, and industrial sectors. Through its utility programs, the firm supports large commercial portfolios where identifying energy-saving opportunities was becoming harder.
A Portfolio Too Diverse for Traditional Audits
Traditional audit methods limited the scale and speed of energy efficiency program delivery. The client wanted to build an intelligent, data-driven solution to assess diverse businesses, identify eligible sites, and target energy-saving initiatives.
01
Manual Audit Process
Commercial energy assessments depended on physical site visits. Manual audits made energy efficiency programs slower and more expensive to deliver.
02
Reactive Program Delivery
Utilities relied on customer participation, limiting program reach and the ability to prioritize commercial establishments with the highest energy-saving potential.
03
Fragmented Data Ecosystem
Business data from utility billing, building permits, assessor databases, and equipment registrations existed across multiple systems. This created data silos, slowed analysis, and increased manual reconciliation.
04
Limited Equipment Visibility
Utilities lacked a centralized view of energy-intensive assets such as pools, modulating valves, and aging HVAC units. Identifying energy-saving opportunities therefore required individual building inspections.
Automating Commercial Energy Assessments
We built an AI-powered energy advisor web application on the client’s existing enterprise data foundation. The Energy Advisor Solution used AI-driven analytics to automate commercial energy assessments, identify eligible businesses, and generate personalized energy-saving recommendations across the utility portfolio.
01
Unified Enterprise Data Foundation
Consolidated utility billing, building permits, assessor data, and equipment registrations into one integrated data foundation.
02
Vision-LLM Equipment Intelligence
Used vision-LLM to identify energy-intensive equipment without physical site inspections.
03
Intelligent Business Assessment
A business analysis agent combined enterprise data and equipment insights to automate commercial energy assessments.
04
Portfolio-Level Benchmark Analytics
Portfolio analysis agent benchmarked businesses across sectors, states, and counties. The analysis highlighted high-potential commercial accounts for energy savings.
05
AI-Driven Recommendation Engine
The recommendation agent identified eligible businesses and generated targeted energy-saving recommendations.
The Results of Portfolio-Wide Energy Analysis
100% Account Coverage
Utilities assessed every commercial establishment in their territory within days, replacing years of sequential physical audits.
30-50% Conversion
Prioritizing the top 10–15% of high-potential accounts increased participation and program conversion.
~95% Lower Lead Cost
AI-based business and equipment analysis reduced lead identification costs from $300–$500 to $10–$20 per lead.
30% Customer Satisfaction
Personalized energy-saving recommendations improved customer engagement and satisfaction across commercial energy programs.
How We Make Technology Work for You
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