For decades, building data has lived behind dashboards. Owners and operators have stared at rows of charts, dials, and trend lines, convinced that visibility equals understanding when seeing without context isn’t actually intelligence, it’s distraction. 

According to our CTO, Phil Mounsey-Smith, when Bitpool first started, the issues were traditional, like connecting buildings, extracting reliable data and presenting it so it was easy to understand. Dashboards made sense in that era. They gave engineers and operators a way to visualise what was happening inside complex systems. 

But as Phil explains, that approach had limits. “We were building mechanical interfaces for mechanical systems,” he says. “They showed you what was happening, but not why. They didn’t conform to the way humans actually think and make decisions.” 

That realisation set the foundation for Bitpool’s shift toward AI-driven conversation. Helping buildings to talk and be heard. 

AI with a difference 

Since large language models (LLMs) and GPT-based technology have risen in popularity, the way we interact with systems has fundamentally changed. We’ve moved from mouse clicks to natural language and from “query” to “conversation”. Instead of trawling through tabs and widgets, Bitpool users can now ask simple questions by voice or by text. 

“AI lets us design systems that conform to people,” says Phil. “The technology should adapt to the user, not force the user to adapt to the technology.” 

“Find out today which system used the most energy overnight” or “where’s the anomaly in my HVAC data?” 

From insights to intuition 

Efficiency is great, but the interpretation that comes from AI, means it’s better than human insights in many ways. It highlights patterns a human might overlook, uses historical data patterns to fill gaps and uses all of that to provide real time recommendations in seconds.  

“Buildings generate terabytes of data every day,” Phil says. “No human can process that volume meaningfully. With AI, we can finally unlock what that data has been trying to tell us all along. Our buildings are speaking, and we’re all listening!.” 

Trust and context 

It goes without saying that AI driven dialogue is only meaningful when the data underneath it can be trusted. That’s where our data assurance framework comes into its own, cleaning, validating, and fingerprinting every sensor stream before it’s ever analysed. 

“AI is only as smart as the data you feed it,” Phil explains. “Our role is to engineer for confidence, making sure that when AI gives an answer, it’s grounded in reality and fact.” 

By calculating completeness, uniqueness, and accuracy scores for every inbound data stream a fingerprint is created for every element, allowing AI to use a source of absolute truth to deliver insights with measurable confidence. 

The human element 

For all the technical complexity behind our platform, Phil is proud that our purpose remains simple – to change the way buildings are managed by making them easier to understand and operate. 

Phil sums it up best: “Technology should disappear into the background. When we get it right, the focus shifts back to people at all levels making better decisions faster. That’s the measurable performance gain from real building intelligence.” 

Ultimately, we believe the future of building intelligence is about conversation and impact, not dashboards. 

“We’re not about chasing trends, we’re all about the fundamentals, helping our community to be better my making data visible, accessible, and actionable”, says Phil.