Butlr vs Occuspace: A Head-to-Head Comparison

Butlr and Occuspace both show up on shortlists for teams trying to understand how their spaces are being used. In higher education in particular, the two tend to land on the same evaluation. Both platforms lead with privacy, both claim fast deployment, and both have campus and enterprise logos behind them. This surface-level overlap makes it harder to see where they differ.
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Occuspace emphasizes install speed and low total cost of ownership, using passive Bluetooth Low Energy (BLE) and Wi-Fi scanning in its Macro sensors and mmWave radar in its Micro sensors to detect activity in a space. Butlr has a thermal occupancy intelligence layer, anonymous by hardware design, paired with an API-first architecture built to dock into the systems organizations already use rather than become another platform to manage.
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Those are two distinctly different foundations, and the differences add up across what each platform counts, where it can be deployed, how it scales across a portfolio, and what your data looks like when it gets to the teams who need to act on it. 
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Butlr Overview

Butlr is a thermal occupancy intelligence platform that helps enterprise organizations understand how their buildings are being used. It serves workplace, higher education, senior living, retail, and laboratory environments across 22 countries. Customers include Carrier, Qualcomm, Lendlease, Snowflake, and Georgia-Pacific.
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Butlr provides an infrastructure layer for the built environment, feeding occupancy analytics into the systems an organization already runs. The sensing hardware captures thermal data only, enforcing privacy at the physical level. The platform currently covers 100 million+ square feet through 30,000+ deployed sensors.
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Thermal Sensing That Counts People, Not Devices

Butlr's Heatic sensors read thermal energy to detect the presence of people in a space. The output is a direct headcount.
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Wi-Fi and BLE scanning infer occupancy from the number of broadcasting devices in range. For example, a student carrying a phone, laptop, tablet, and smartwatch can look like four people, while a visitor whose phone is on airplane mode can look like zero. Thermal sensing avoids this problem entirely, because people emit heat whether or not they're carrying electronics.
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One Sensor, Two Modes

Each Butlr sensor can operate in either presence mode or traffic mode, selectable per deployment. Presence mode maps where people are within a room or zone, down to individual coordinates, and tracks dwell time.
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Traffic mode counts entries and exits across a defined threshold, giving floor-level or building-level occupancy totals. One piece of hardware covers both use cases, so teams don't need to purchase and manage separate sensor types for different spaces.
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Privacy-First by Hardware Design

Butlr's sensors capture thermal data only and cannot produce images, device signals, or personally identifiable information. The platform is SOC 2 Type II certified, and it clears legal, InfoSec, and works council scrutiny in regions where signal-based sensing raises flags. This also opens up spaces where other technologies face restrictions, including restrooms, patient rooms, labs, and senior living facilities.
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API-First Architecture

Butlr feeds occupancy data into the tools teams already use. REST APIs and webhooks push data in real time to integrated workplace management systems (IWMS), building management systems (BMS), BI tools like Tableau and Power BI, and cleaning or energy platforms.
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Built for Enterprise-Scale Deployment

The sensors are wireless and battery-powered. They don't require electricians, ceiling work, or conduit runs. Connectivity runs through Butlr's Hive gateway, which supports Wi-Fi, cellular, and ethernet. Most organizations go from order to usable data in roughly five weeks.
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Occuspace Overview

Occuspace is an occupancy intelligence platform built for higher education, corporate real estate, and federal environments. The company launched in 2017 out of UC San Diego, where its founders built the first version to help students find open seats in campus libraries. It has since expanded to corporate and government clients including Google, Sodexo, Georgia Tech, and Baylor University.
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Key Features

• Passive BLE and Wi-Fi Scanning (Macro Sensors): Occuspace's Macro sensors passively detect Bluetooth and Wi-Fi signals from smartphones, laptops, and wearables in range. The system infers how many people occupy a space based on the number of active devices. Each Macro sensor covers roughly 2,000 to 3,000 square feet depending on layout.
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• mmWave Radar (Micro Sensors): Occuspace's Micro sensors use mmWave radar to detect presence and count occupants in smaller, enclosed spaces like meeting rooms and phone booths. Each Micro sensor covers approximately 400 square feet.
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• Wall Socket or PoE Installation: Each sensor plugs into a standard electrical outlet or connects via Power over Ethernet (PoE) cabling and requires no ceiling mounting, hardwiring, or electrician. Install time per unit is near zero.
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• Cloud Data Platform: Occuspace aggregates observations across a portfolio through its data platform, which includes a portal, API access, and digital signage integrations. The platform processes terabytes of data monthly, backed by more than ten years of calibrated occupancy observations.
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• Federal Readiness: Occuspace offers a dedicated federal solution for environments where cameras and imaging sensors are prohibited. Through a partnership with The Building People, The Building People holds a five-year General Services Administration (GSA) blanket purchase agreement covering 180 million+ square feet.

Advantages

• Occuspace has an established presence on campuses, with deployments at UCSD, Georgia Tech, NC State, Baylor, UCSB, and the University of Ottawa. The founders built the platform for academic space utilization from the start. The platform's sensor hardware also carries a lower per-unit price point.
• The platform's sensor hardware carries a lower per-unit price point, with reported total cost of ownership (TCO) 3–5x below competing alternatives. For teams evaluating on hardware cost alone, this can be a meaningful factor in early-stage budgeting.

Shortcomings

• The Macro sensors infer occupancy from the number of broadcasting devices in a space. Accuracy depends on how many devices each person carries and whether those devices are actively transmitting. In spaces with high device-to-person ratios or visitors without connected devices, counts can drift from true occupancy.
• Macro sensors require a wall outlet or PoE connection. In older buildings, historic campuses, or retrofits where power placement doesn't align with coverage needs, this creates gaps or forces workarounds like extension cords.

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A Side-by-Side Comparison of Butlr and Occuspace

The comparison below breaks down how Butlr and Occuspace differ across the categories that matter most in an evaluation.
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Sensor Technology

Butlr's thermal sensors measure body heat to produce a direct headcount of the people in a space. Occuspace's Macro sensors scan for Bluetooth and Wi-Fi signals from nearby devices and use that activity to estimate occupancy. Its Micro sensors use mmWave radar to detect presence in smaller rooms.
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One tells you how many people are present, while the other primarily tells you how many broadcasting devices are present.
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Key Takeaway: In a stable corporate office with predictable device ratios, Occuspace's device-based counts can track occupancy trends effectively. Campus environments break that model. Students carry three or four devices each, visitors aren't on the network, and spaces turn over constantly. For academic or mixed-use buildings, Butlr's thermal sensing produces a more reliable count.
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Connectivity Options

Butlr sensors connect through a dedicated Hive gateway that supports Wi-Fi, cellular, and ethernet backhaul. Teams choose the connection path that fits each building, and can use cellular in locations where the local network is restricted or unavailable.
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Occuspace sensors plug into wall outlets and transmit data through the building's existing network. In most modern offices, this is straightforward. In buildings with restricted networks or limited IT support, connecting new devices can add coordination that slows rollout.
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Key Takeaway: Getting data to the cloud isn't the issue for either platform. The difference shows up when local network access is slow to provision or restricted at certain sites. Butlr's cellular backhaul gives deployment teams a way around that dependency.
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Anonymous Data Capture

Both Butlr and Occuspace are camera-free, and neither stores raw personal identifiers. The difference is that Butlr's occupancy sensors read thermal energy only. The hardware lacks the components to capture images, device signals, or any data point that could identify a person.
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Occuspace's sensors passively receive Bluetooth and Wi-Fi signals from nearby devices and use MAC address randomization to avoid storing raw identifiers. But some EU regulators and InfoSec teams treat randomized MAC addresses and device signal patterns as personal data under certain conditions. The mmWave radar component also draws the same scrutiny that works councils apply to other radar-based sensing systems.
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Key Takeaway: Both platforms avoid cameras and raw identifiers, but the mechanisms differ. Butlr's privacy case rests on hardware physics, while Occuspace's rests on data-handling practices. Under EU privacy regulations, works council reviews, or strict InfoSec requirements, Butlr is the simpler case to make because there's nothing to govern.
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Installation Timeline

Both platforms install faster than wired ceiling-mounted alternatives. Occuspace's plug-in sensors go directly into wall outlets, and a team can cover a floor in hours where wall power is abundant.
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Butlr's wireless, battery-powered sensors don't depend on outlet placement, which removes a constraint that surfaces quickly across older buildings, campus retrofits, and any space where outlets don't line up with coverage needs.
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Key Takeaway: Occuspace's plug-in model is hard to beat on speed in a single modern office with plenty of wall outlets. Campus portfolios span decades of building stock where outlet placement is unpredictable, and Butlr's wireless sensors deploy consistently regardless of building type, making them a better fit for multi-building or multi-campus rollouts.
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Accuracy

Occuspace claims 95% accuracy, derived from aggregate counts under favorable conditions. Yet per-space performance can vary depending on the environment, and the 95% figure is a portfolio-level benchmark.
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Occuspace's device-based approach introduces additional accuracy risks beyond multi-device overcounting. For example, abandoned devices register as occupancy in empty rooms, and Wi-Fi traffic from adjacent spaces can bleed into a room's count. These distortions hit hardest in the dense, high-turnover campus environments where both platforms compete.
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Butlr avoids these failure modes entirely because its sensors read heat. An empty room with a forgotten laptop reads as empty.
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Key Takeaway: Occuspace's 95% figure can hold in stable environments, but the conditions that erode per-space accuracy (multi-device users, abandoned devices, Wi-Fi bleed from adjacent rooms) are routine on campus. For capital decisions or space consolidation, Butlr's thermal count is the safer foundation.
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Integrations

Butlr delivers occupancy data through REST APIs and webhooks that feed IWMS, BMS, BI tools, and cleaning platforms directly. 

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Occuspace offers API access, but the product experience centers on its own data platform, portal, and digital signage tools. 

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‍Key Takeaway: Butlr is built to integrate into your existing stack. Occuspace is built to be the stack. If your organization already runs on IWMS, BMS, or BI platforms and wants occupancy data inside them, that distinction will influence your decision.
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Price

Occuspace's 3–5x lower TCO advantage is benchmarked against other occupancy sensing solutions, including wired, ceiling-mounted systems that require electricians, conduit, and structural work. Against wireless thermal sensing, which eliminates those same costs, the comparison tightens.

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Full-portfolio TCO goes beyond sensor price. Coverage per square foot, installation labor, time to first data, ongoing maintenance, and integration cost all contribute. So does the cost of making space-planning or capital decisions on occupancy data that doesn't reflect true utilization.

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‍Key Takeaway: Per-sensor hardware cost favors Occuspace. Across a full portfolio, though, TCO includes deployment flexibility, integration overhead, and the consequences of acting on inaccurate counts. On that basis, Butlr is cost-competitive and delivers data you can build a business case on.

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Overall Assessment

Occuspace has real strengths in plug-in install speed, per-unit hardware cost, and an established campus presence. For standard office buildings with abundant wall power and predictable device density, it can deliver useful occupancy trends with minimal deployment friction.
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But across the categories that matter most for campus and portfolio-scale decisions, Butlr brings a stronger foundation. For most organizations evaluating occupancy sensing today, including in higher education, Butlr is the stronger choice.
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Choose Butlr if...

• You need occupancy data based on real presence, not the devices people happen to be carrying, particularly in dense-device or high pass-through spaces like lecture halls, libraries, and common areas.
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• You're measuring a campus or mixed portfolio that spans decades of building stock, where outlet placement, historic construction, or retrofits make plug-in deployment impractical.
• Your spaces include sensitive or restricted areas (restrooms, labs, patient rooms, residence halls, senior living) where capturing identifiable signals is a problem.
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• Privacy compliance is nonnegotiable and you need a solution that passes legal, InfoSec, and works council review based on hardware physics, not data handling policies.
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• You want occupancy data flowing into the systems you already use (IWMS, BMS, BI tools, cleaning platforms, campus space-management systems) rather than staying inside a vendor's proprietary platform.
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• You're planning around capital projects, space consolidation, or utilization decisions where the cost of acting on inflated or inaccurate counts is high.
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• You need a partner that supports staged, multi-site or multi-building rollouts across large portfolios without steep cost increases per square foot.

Choose Occuspace if...

• Your spaces are concentrated in standard modern buildings with abundant wall power and predictable device density.
• You're solving a federal use case where their GSA channel and camera-prohibited positioning are a direct fit.
• You're comfortable inferring occupancy from device signals and don't need presence-based counts for the decisions you're making.
• Your team is willing to work primarily inside Occuspace's portal and data platform environment rather than integrating data into a broader operational stack.
• Per-sensor hardware cost is the dominant factor in your evaluation, ahead of accuracy fidelity, integration flexibility, or deployment universality.

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See How Butlr Fits Your Organization

For organizations evaluating occupancy sensing platforms, the best next step is to see how the data works in the context of your specific spaces, portfolio, and existing tech stack.

Request a demo to see how Butlr works with your buildings and systems.