Design Workplaces that Support Modern Ways of Working

Using real occupancy data, not surveys or assumptions, to decide how space should be configured. VergeSense combines continuous measurement with AI-powered scenario modeling, so you can predict how a layout will perform before you build it, and verify the actual results after changes are made. This replaces one-time design surveys with a living model that gets more accurate as real usage data comes in, so every layout decision is grounded in behavior, not guesswork.

Yes. Upload any floor plan and predict how your workforce will use it before a single wall moves. Compare your current layout against multiple redesign options side by side, and see projected utilization, capacity, and experience impact for each in minutes, not the months a traditional design study would take. This lets you validate a layout decision with data before committing capital.

Active occupancy is when someone is physically present in a space. Passive occupancy is when a space is claimed by personal belongings, a laptop, bag, or jacket, but the person has temporarily left. VergeSense is the only platform that detects both. Without passive occupancy data, teams make space decisions based on half the picture, often overestimating true availability and underestimating real demand.

Allocating zones to teams based on actual work patterns, not just headcount ratios. VergeSense measures how each team really uses its assigned space, identifies imbalances where one team is overcrowded while another sits underused, and models alternative allocations before you make any physical changes. This turns team stack planning from a headcount spreadsheet exercise into a behavior-grounded decision.

A ghost booking is a room reservation where no one showed up, or where attendees left without releasing it. VergeSense detects them by comparing your booking system data against actual sensor or WiFi occupancy data in real time. The platform then quantifies how often this happens and what it costs by room, floor, and building, so you can target the specific spaces driving perceived scarcity.

Real occupancy data is overlaid directly on your interactive floor plans, showing which zones are heavily used and which sit empty, broken down by day, time of day, or custom period. Instead of relying on anecdotes about which areas "feel busy," heatmaps give workplace and design teams a visual, data-backed way to see exactly where space is working and where it isn't.

Yes. Track before-and-after utilization at the space, floor, and neighborhood level to see exactly how a redesign changed behavior. Rather than waiting for the next annual survey to find out if a change worked, you can A/B test configurations continuously and adjust in near real time, turning workplace design into an ongoing feedback loop instead of a one-time bet.

No. You can start with Predictive Planning using just a floor plan, no sensors required, since the Large Spatial Model generates forecasts from behavioral benchmarks. For measurement, mix sensors, WiFi, and booking data based on your specific goals and budget, adding precision only where the decision in front of you actually needs it. Sensors are an upgrade path, not a prerequisite.

Surveys capture what people say they do. Occupancy data captures what they actually do. The two often diverge significantly, and that gap is where bad space decisions come from. VergeSense measures real behavior continuously rather than at a single point in time, and Predictive Planning models future performance using 250M+ sq ft of real behavioral data, not opinions collected once a year.

Yes. VergeSense data is frequently shared with architecture and design partners to inform everything from minor reconfigurations to full redesigns. Design firms use occupancy and utilization data to validate assumptions about how space types and neighborhoods actually get used, replacing guesswork with evidence early in the design process, before drawings turn into construction costs.