Butlr

For the last two decades, the smart-building industry has tried to do one thing: figure out how people actually use space. Cameras counted heads. Wi-Fi pings inferred presence. Badge scans tracked entries. Beacons triangulated movement. Each layer captured more data, and each layer added something the industry quietly hoped no one would notice — a camera in the ceiling, a tracker in the badge, a feed sitting on a server that someone, somewhere, could pull up.

The buildings knew they were full. They never really knew how they were being used.

Anyone who has watched a Fortune 500 try to make a real-estate decision with the data they actually have — a badge system that misses 30% of the floor, an occupancy camera the works council vetoed, a Wi-Fi heuristic that thinks a forgotten laptop is a person — knows the issue. Post-COVID hybrid work blew up every prior assumption about how offices, labs, classrooms, and care facilities operate. Sustainability and energy regulation made occupancy data a compliance requirement. And in the middle of all of it, privacy expectations from employees, residents, students, and patients have only sharpened. The old data sources can't meet the new bar.

The Opportunity: Spatial Intelligence Without Surveillance

The built environment needs a sensing layer that solves the underlying problem — ambient, accurate, real-time understanding of how people occupy and move through space — without the tradeoffs that have held the category back. Cameras are too invasive for most environments where the data is most valuable: workplaces with works councils, senior living communities, hospitals, schools, labs. Wi-Fi and badge data are too lossy and too dependent on infrastructure the building owner doesn't always control. The right answer has to be ambient by default, anonymous by construction, and easy enough to retrofit into buildings that already exist.

The technology to do that finally exists.

The next layer of building intelligence isn't another camera. It's a sensor that can only see what matters — and is incapable of seeing anything else.

A Thermal AI Layer for Every Building

Butlr's platform pairs proprietary wireless thermal sensors (Heatic 2 and Heatic 2+) with an AI platform that turns body heat into structured spatial intelligence. The sensors are camera-free, peel-and-stick, battery-powered, and capable of running for years on a single charge. They detect presence, headcount, posture, activity, and movement at high fidelity — and by design, they cannot capture personally identifiable information. Their platform does three critical things:

1. Sees the space, not the person. Low-resolution thermal data captures occupancy, posture, and activity with high accuracy while remaining incapable of identifying who's there. Privacy-by-construction — not a policy, an architecture.
2. Deploys in hours, not months. Wireless sensors mean no conduit, no contractors, no construction permits. Ideal for multi-building rollouts and retrofits of existing real estate.
3. Plugs into the systems enterprises already run. An API-first platform feeds occupancy data directly into workplace tools, facility management systems, HVAC controls, cleaning schedules, and care alert platforms.

The result is a foundational data layer for the built environment. Workplace teams use it to right-size real estate and redesign offices around how people actually work. Senior living operators use it to detect falls and monitor resident wellbeing without putting cameras in private rooms. Universities optimize classroom utilization. Labs prove regulatory compliance. Smart-building operators cut HVAC energy costs by tying setpoints to real occupancy rather than schedules.

Today Butlr operates at meaningful scale: 30,000+ deployed sensors, 1 billion data points per day, 100M+ square feet of coverage, and 200+ global enterprise customers across 22 countries, including Georgia-Pacific, Carrier, Ricoh, Qualcomm, Lendlease, Snowflake, Zscaler, and Envoy, with deep presence in the U.S., Japan, and Europe. The platform has been recognized with industry awards from Fast Company and Inc., and is increasingly the layer that partners — from nurse-call systems to corporate cleaning platforms — build on top of through the Butlr API.

Why We Invested

Hyperplane led Butlr's pre-seed and seed on a single thesis: the next generation of building intelligence would be ambient, anonymous, and built specifically for the realities of how people actually use space. Six years in, three things had to be true at the same time, and they finally are:

• Buildings are being rethought from scratch. Hybrid work, sustainability mandates, and an aging population have made every owner of every building — office, lab, campus, care facility — a buyer of better occupancy data. The category went from "nice to have" to "compliance and P&L."
• Privacy is a feature, not a constraint. As works councils, regulators, and individuals push back on camera-based monitoring, "camera-free by construction" went from a hard sell to the only acceptable answer in the highest-value environments.
• The hardware finally exists. Thermal sensing, edge AI, and low-power wireless have crossed the cost and battery-life thresholds needed to make stick-on, multi-year, building-scale deployment economical. What required wired infrastructure five years ago now ships in an envelope.

Honghao Deng and Jiani Zeng spun Butlr out of the MIT Media Lab in 2019, then spent the next six years doing the harder thing: turning a research-grade thermal sensing platform into hardware that holds up for years on a battery in a real ceiling, in a real building, in 22 different countries. Both were named to Forbes 30 Under 30 for the work. The combination of physical AI depth and enterprise discipline is what made this a category, not a project.

Cameras see everything. Butlr sees only what matters.