
Meet Butlr
Discover what spatial intelligence can do for you.
Thank you! Your submission has been received!
What are occupancy insights?
Occupancy insights are analyzed measurements of how people occupy and move through a space, combining metrics like presence counts, seating patterns, dwell times, and usage trends to inform workplace decisions.
- Occupancy rate: Percentage of available seats or rooms occupied during a given time.
- Utilization: How effectively a space is used relative to its potential capacity.
- Ambient intelligence: Systems that sense and respond to presence and activity using non-intrusive sensors.
- Anonymous sensing: Data collection methods that do not identify individuals, preserving privacy while capturing aggregate patterns.
Butlr is one example of an ambient intelligence provider using heat-based, camera-free sensing to deliver anonymous, real-time occupancy and activity insights for buildings.
Why actionable occupancy insights matter now
Hybrid work, rising real estate costs, and sustainability goals make space optimization a strategic priority; actionable insights convert data into specific, timed recommendations.
- Reduce cost: Identify underused areas to repurpose or consolidate and lower lease and operating expenses.
- Improve employee experience: Align space with actual needs by providing more collaboration zones and reducing unused fixed desks.
- Boost sustainability: Match heating, cooling, and lighting to real occupancy to save energy and emissions.
- Support operations: Optimize cleaning, maintenance, and staffing using real demand rather than schedules.
Actionable insights specify what to change, where, and by how much.
How occupancy data is collected (responsibly)
Choose sensing approaches that balance accuracy, privacy, and installation complexity and prioritize anonymous, camera-free methods where possible.
- Thermal and heat-based sensors: Detect presence and movement without capturing images, supporting anonymous sensing.
- Infrared and motion sensors: Provide presence and movement counts for high-level occupancy data.
- Badge and booking systems: Offer scheduled usage data but may miss actual presence or shared-use patterns.
- Wi-Fi and Bluetooth analytics: Infer device presence but can be noisy and raise privacy concerns.
Best practice is to validate sensors across different lighting and furniture conditions and combine multiple sources for richer context while preserving privacy.