You Own the Stack Plan. And Everything That Happens After.

VergeSense supports its own Infinity area sensors, badge data, videoconferencing data, Wi-Fi occupancy data, space booking platforms, and calendar integrations, so you're never locked into a single measurement method. All sources are automatically reconciled and de-duplicated into a single unified occupancy model, meaning you don't have to manually cross-reference conflicting numbers from different systems. You can start with whatever data you already have and layer in additional sources as your planning needs grow.

The Infinity sensor delivers 95% accuracy with AI-enabled passive occupancy detection that captures meaningful presence, not just motion, the kind of accuracy that makes the data reliable enough to base planning decisions on. It has a 10-year battery life with no maintenance required, and supports both wired and wireless deployment depending on your building's infrastructure. Most enterprise deployments are completed within one to two days per site.

Passive occupancy means detecting that a space is in use even without active human motion, belongings at a desk, a laptop open, a jacket on a chair. Traditional motion sensors miss this entirely, undercounting real occupancy and making a space look available when it's actually claimed. VergeSense's AI-enabled passive detection captures the full picture, which matters most when that undercounting leads teams to release or reassign space that's genuinely in use.

Predictive Planning identifies the specific attendance threshold at which each space type hits behavioral capacity, the point where employee experience starts to degrade even though the space technically isn't full. This uses probabilistic forecasting rather than simple averages, so you see risk levels at different confidence intervals instead of a single number. That distinction matters because a floor with 252 design capacity might realistically break at 128, and averages alone would never surface that.

Yes. Upload a floor plan and workforce assumptions, and Predictive Planning generates forecasts based on 250M+ sq ft of real behavioral data, no hardware required to get a defensible starting point. Adding sensors later upgrades your forecasts from modeled precision to measured precision, sharpening accuracy as real data comes in. Most teams start this way and layer in measurement only where a specific decision demands it.

The Large Spatial Model is VergeSense's proprietary AI model, trained on 250M+ sq ft of real workplace behavior across 200+ enterprises in 50+ countries, making it the only spatial AI model of its kind. It powers Predictive Planning and the Meridian Platform by running 1,000+ Monte Carlo simulations per scenario to produce probabilistic demand forecasts, capacity risk analysis, and space mix recommendations grounded in real behavior rather than theoretical planning ratios.

Data is available from portfolio level down to individual spaces: portfolio, building, floor, neighborhood, zone, space type, and individual space, so you can analyze at whatever altitude a given decision requires. You can view trends by hour, day, week, or custom periods, which matters when a space looks fine on a weekly average but is actually failing badly every Tuesday afternoon.