Test the Decision Before You Commit

Predictive Planning is the Meridian Platform’s AI-powered planning capability that helps enterprise real estate and workplace teams forecast space demand, model scenarios, and make portfolio decisions before committing capital. Unlike traditional planning studies, spreadsheets, or static space ratios, Predictive Planning runs continuously, updating automatically as attendance patterns shift, headcount changes, or lease events approach. It replaces the consultant engagement model with a planning engine your team owns and operates.

The Large Spatial Model (LSM) is VergeSense's proprietary foundational AI model, purpose-built to understand how humans use physical space. Trained on 8 years of real-world occupancy behavior across 250M+ square feet of workplaces, across industries, geographies, and space types, it's the only spatial AI model of its kind. The LSM is what enables the Meridian Platform to forecast occupancy for unmeasured spaces, identify risk thresholds, and run scenarios grounded in real behavioral patterns, not theoretical assumptions.

No. Predictive Planning is designed to deliver value from day one with data you already have. Booking systems, badge access, videoconferencing data, and WiFi analytics are all sufficient to begin generating forecasts and running scenarios. For spaces without any measurement infrastructure, the Large Spatial Model can forecast occupancy patterns using behavioral benchmarks calibrated to your industry and building type, or even based on buildings in your portfolio. Sensors can be added over time to increase precision at the space level, but they're never a prerequisite.

Yes. The Meridian Platform integrates natively with major space booking platforms, so your reservation and utilization data flows directly into the planning tool. Booking data is particularly valuable for understanding ghost meeting patterns, policy compliance, and the gap between reserved and actually used space, all of which sharpen your demand forecasts.

Yes. WiFi analytics and badge access data are both supported as occupancy inputs in Meridian. WiFi provides building and floor-level people count at up to 85% accuracy, while badge data gives you entry and exit patterns by location. Either source, or both combined, gives the Large Spatial Model enough signal to begin generating meaningful demand forecasts and scenario outputs.

For teams starting with existing data sources like booking systems or WiFi, implementation is typically measured in days, not weeks. There's no hardware deployment required to get started. Teams with occupancy sensor data already flowing into the Meridian Platform can run their first scenario within hours of enabling Predictive Planning. Full enterprise rollouts with multiple data source integrations vary by complexity, but VergeSense's implementation team is structured to get you to first value quickly.

Predictive Planning is part of the VergeSense Meridian platform. It's available to customers as part of their Meridian subscription, with packaging that scales to the size and complexity of your portfolio. Contact our team for details on how Predictive Planning is structured for your specific use case.

Predictive Planning is built for enterprise corporate real estate, workplace, and occupancy planning leaders who are responsible for portfolio strategy, space optimization, and capital planning decisions. It's particularly valuable for teams managing large, multi-location portfolios where the cost of a wrong lease or design decision is significant, and where the speed and frequency of planning decisions has outpaced what traditional consulting models can support.

Most IWMS platforms are built to manage and record what exists, like leases, assets, reservations, maintenance, not to forecast what's coming. Predictive Planning is built specifically for forward-looking decisions: demand forecasting, scenario modeling, and risk identification. The Large Spatial Model gives the Meridian Platform a level of spatial intelligence that no IWMS planning module can replicate, including the ability to simulate occupancy for unmeasured spaces and identify experience risk thresholds by team and floor.

Yes. Because the Large Spatial Model is trained on 250M+ square feet of real workplace behavior across industries and geographies, it can generate occupancy forecasts and scenario models for locations where you have no existing measurement data. Using behavioral benchmarks calibrated to your industry, work patterns, and team size, the Meridian Platform can help you right-size a new location before you sign, so you're not committing to square footage based on assumptions alone.