AI-Driven Platform for Reducing Cost, Consumption & Carbon
The challenge
Managing energy across large portfolios is complex, fragmented, and error-prone. Traditional systems bombard teams with raw data but offer little clarity, context, or reasoning behind rising costs and consumption. Decision-makers struggle to see what’s happening, why it’s happening, and what to do next — leading to wasted energy, higher costs, and missed opportunities.
Large building portfolios struggle with:
[ Human error ] — manual data entry and siloed systems create mistakes and inefficiencies.
[ Lack of visibility ] — managers can’t easily see real-time cost, consumption, or anomalies across all their properties.
[ No context behind numbers ] — alerts may flag problems but don’t explain “why” or “so what.”
[ Complex tools ] — existing platforms require expensive hardware and technical expertise.
Impact of the problem: high operational costs, energy waste, and missed sustainability targets.
the Process
Understanding Our Users
Conducted surveys, interviews, and usability tests, uncovering 3 core user types — Building Owner, Building/Portfolio Manager, Building Operator — with distinct goals:
[ Building / Portfolio Owner ]
[ Goal ]
Monitor costs, consumption, and sustainability across multiple properties at a glance.
[ Context ]
Owns large mixed-use portfolios, limited time to dive into details.
[ Need ]
Quick, high-level overview of financial and environmental performance.
[ Frustration ]
Human error and delayed reporting reduce confidence in data.
[ Building / Community Manager ]
[ Goal ]
Ensure all facilities operate within budget and standards.
[ Context ]
Oversees multiple buildings or a large compound, manages staff and maintenance.
[ Need ]
Real-time alerts, budget tracking, and insight into operational efficiency.
[ Frustration ]
Manual processes and fragmented systems make it hard to track performance.
[ Building Operator ]
[ Goal ]
Run day-to-day operations smoothly and react to anomalies quickly.
[ Context ]
Works on-site, monitors multiple systems (HVAC, meters, equipment) during shifts.
[ Need ]
Clear, actionable alerts and contextual insights to reduce investigation time.
[ Frustration ]
Too much raw data and unclear priorities slow response time.
The Solution
cMatter is an AI-powered SaaS platform designed to:
Give real-time visibility of cost, consumption, and carbon footprint.
Provide AI insights that go beyond alerts, showing context, patterns, and actionable takeaways.
Scale from basic visibility to predictive analytics and automation (phased roadmap).
Work with minimal hardware (smart meters and existing sensors).
