An Energy Efficiency Platform - it’s been built with the idea of most EMS platforms out there just give out the data. Throughout my research and development of the application, we want to build a user-client focused implementation of our take on the ASHRAE standards into a scalable and implementable workflow of a Web Application.
Basically: energy bills rising, energy costs restructured and companies tracking down their financials to the cent but their energy consumption is always a mystery. Some random spike in production would result in a higher energy bill - but this still isn’t able to be budgeted. Where is the energy going? Which machines are wasting power? When should we run equipment to save costs? These aren’t just operational questions—they’re the difference between profit and loss, between sustainability goals met and missed.
The biggest gap in solving this isn’t technology—sensors and meters exist. It’s making sense of the noise. Energy data streams in from hundreds of devices, but without context, patterns, or actionable insights, it’s just numbers on a screen. Facilities need three things: visibility into what’s happening, intelligence to understand why, and automation to act on it. Right now, these live in separate worlds: monitoring systems show graphs, consultants analyze spreadsheets, and decisions happen in boardrooms weeks too late.
What is IoTWatt?
IoTWatt is an AI-powered energy management platform that turns raw sensor data into savings. We monitor industrial and commercial facilities in real-time, discover inefficiency patterns through machine learning, and automate demand control to reduce electricity costs by 20-30%.
Instead of just showing you graphs, we tell you what’s wrong, which equipment is causing it, and how much money you’re losing. Then we help you fix it—sometimes automatically.
Think: energy monitoring that actually thinks.
The Vision
The goal isn’t just to monitor buildings—it’s to make them learn. A facility that knows when machines are wasting power before you do. A system that shifts loads to cheaper electricity windows without being told. Analytics that attribute every ringgit of savings back to specific actions, so CFOs see ROI in their language and engineers see actionable next steps in theirs.
We’re building toward a world where energy efficiency isn’t a quarterly project—it’s automatic. Where facilities run themselves smarter every day, where sustainability targets are met not through audits and retrofits, but through continuous micro-optimizations happening in the background. Where the question shifts from “How much energy did we use?” to “How much money did we save today, and what’s the plan for tomorrow?”