Operating at the intersection of science, engineering, and purpose 

AI is all the rage everywhere you look, and it is no different in building management systems either. The challenge is implementing it in a manner that is meaningful. And perhaps more pertinently, rolling it out at scale across infrastructure that was never built with it in mind. We catch up with Garima Bharadwaj, Co-founder & CTO, Enlite, to understand more about this fast-growing category, and the trajectory it might take. 

AI-driven building management is still an emerging category in India. What are the biggest technical and adoption barriers preventing wider deployment of intelligent infrastructure, and how does the industry need to evolve to overcome them? 

For decades, buildings ran on binary, pre-programmed logic. The entire decision-making framework was “if temperature crosses X, do Y”, and it worked just good enough that nobody questioned it. 

What we introduced at Enlite was something fundamentally different: dynamic decisions driven by AI. A building in Delhi in peak summer heat behaves nothing like a building in Bangalore during monsoon. Those are completely different operational realities, and traditional systems were never built to factor that in. We created a new category. That takes time for an industry to absorb, not because people are resistant, but because the mental model has to shift first. 

What I find genuinely encouraging now is that people are not just open to it, they are coming back to us with tangible possibilities. The conversation has moved from “interesting, let us evaluate” to “here is our building, here is our problem, how do we do this.” That is a meaningful shift. People want to be part of building something real, and that energy is something we feel very directly. 

Traditional building management systems have largely relied on wired infrastructure. How does a wireless-first approach change what’s possible in retrofit scenarios, and what does that mean for India’s massive existing building stock? 

Automation was never an afterthought in buildings. The intention was always there. But the systems that got installed over the years became siloed, often outdated, and completely unable to talk to anything newer. The people who understood those legacy systems moved on, and the institutional knowledge walked out with them. 

So, when you walk into an older building today, you are not starting from zero. You are starting from a place that is much more complicated than zero. That is the real retrofit challenge. 

What wireless and cloud-first architecture changes is that you do not have to rip any of that out. We can integrate with older systems and new systems alike, running them together without disruption. Non-invasive deployment, zero downtime, integrations that come online within minutes, and then the building starts running on intelligent logic from that point forward, independently. 

No drilling, no shutdowns, no asking tenants to vacate. For India’s enormous existing building stock, hospitals, hotels, older commercial complexes, government buildings, that is what makes the opportunity real and actionable today. 

With ESG reporting becoming more rigorous, how should building operators and real estate developers think about quantifying the energy and emissions impact of intelligent systems, and what metrics actually matter? 

The shift I am seeing is that ESG is moving from storytelling to accountability. Investors are asking for numbers, not narratives, and that is actually a good thing for the industry. 

The metric that matters most, in my view, is energy use intensity measured at the zone level, not just at the building meter. That granularity is what separates genuine performance from a good-looking annual report. 

Beyond energy, carbon tied to Scope 1 and Scope 2 consumption, indoor air quality, water use in cooling, these are becoming standard expectations for serious operators. Intelligent BMS makes it possible to report on these with confidence because the data comes straight from the source, continuously, not from estimates made at year end. 

The developers who are getting ahead of this are treating their buildings as ESG assets. The ones who are not will hear about it from their investors soon enough. 

India has historically been a services-led tech economy. What does it take to build a hardware and IP-led deep-tech company here, and how is that landscape shifting for founders working at the intersection of software, sensors, and infrastructure? 

It was, and still is in many ways, an audacious thought to build hardware in India. The history of the country’s tech economy was not built on this. So, when you choose this path, you are choosing it with full awareness that the road involves real experimentation, and failures that are part of the process, not exceptions to it. 

What I have come to believe is that you have to make peace with iteration. Hardware is not a sprint culture. Chips evolve, processing capabilities shift, the underlying technology keeps moving, and your thinking has to move with it every single day. An R&D mindset is not just useful here, it is essential. The spend and the bend of mind both have to be oriented that way. 

The encouraging thing is that India now has genuinely good examples of hardware companies that have been built with conviction and rigor. The ecosystem is shifting. The PLI schemes are bringing serious manufacturing intent. The deep-tech funding environment is more receptive than it has ever been. And there is a growing community of founders who have built globally and come back, which raises the collective knowledge base for everyone. 

At Enlite, we have always believed that building at the intersection of science, engineering, and purpose is where the most meaningful work happens. That has not changed. If anything, the ecosystem catching up around us makes it feel more possible than ever. 

As buildings become more connected, the lines between energy management, occupant experience, and predictive maintenance are blurring. Where do you see intelligent building technology heading over the next five years, and what capability gaps still need to be solved? 

When we started building Enlite, we built the core engine of BMS first. Things like predictive maintenance existed, but they lived separately, as standalone products solving isolated problems. The industry was full of point solutions that never spoke to each other. 

What we understood early is that convergence is not just a feature. It is what gives the whole thing meaning. A building that manages energy in one silo, occupant comfort in another, and maintenance in a third is not a smart building. It is just a building with several expensive dashboards. 

The direction we are headed is a centralized intelligence layer where disparate capabilities come together and inform each other continuously. Energy data influences maintenance decisions. Occupancy patterns shape air quality responses. Space utilization feeds back into how the building is operated and eventually how it is leased. 

The gaps that still need closing are real. Interoperability remains a stubborn challenge across the industry. Cybersecurity for connected building infrastructure is underserved relative to the actual risk. And the AI models need richer, more diverse building data to move from capable to truly reliable. 

The technology direction is clear. What needs to move with equal urgency is the surrounding infrastructure of standards, talent, and regulation.