Right-size Your Portfolio in Hours,
Not Quarters

Occupancy-based portfolio planning uses real-time data on how people actually use office space, rather than historical headcount ratios or lease capacity, to decide where to consolidate, expand, or redesign. It replaces static assumptions with behavioral signals like peak attendance, space-type utilization, and day-of-week patterns. The Meridian Platform takes this further by using the Predictive Planning product to model thousands of scenarios, so teams can right-size with confidence before making any physical changes.

Traditional consultant studies take 3–6 months, cost six figures, and deliver a static report that's outdated by the time it's finished. VergeSense Predictive Planning tool generates scenario-based portfolio plans in hours, not months, powered by a large spatial AI model trained on over 250 million square feet of real workplace behavior. Teams can model headcount changes, lease exits, or hybrid policy shifts side by side and get CFO-ready outputs showing cost impact, capacity breakpoints, and employee experience risk, all without hiring external resources.

You don't need sensors to get started with Predictive Planning. It uses benchmarks drawn from 250M+ square feet of real-world occupancy data to predict how your spaces are likely being used based on your floor plans, headcount, team mix, and region. This gives you a defensible, data-backed baseline on day one. As you layer in sensor, badge, videoconferencing, Wi-Fi, or other data over time, the model refines its predictions to reflect your actual building behavior.

Accuracy depends on the quality of the underlying data and the modeling approach. VergeSense's Large Spatial Model uses Monte Carlo simulations, running 1,000+ scenarios per plan, to produce probabilistic forecasts rather than single-point estimates. This means you get a range of likely outcomes with confidence intervals, not just a guess. When connected to live occupancy data from VergeSense sensors (95%+ accuracy) or Wi-Fi, the forecasts become even more precise because the model learns from how your people actually behave.

Yes. Predictive Planning lets you model any combination of headcount growth or reduction, attendance policy changes, hybrid schedule shifts, and lease decisions. You input the variables, and the model instantly shows the supply-demand impact, including where you'll run out of conference rooms, desks, or focus spaces first. Teams can compare scenarios side by side and quantify the financial and employee experience tradeoffs of each option.

A CFO-ready plan translates occupancy intelligence into financial language: cost savings per scenario, payback timelines, capacity surplus or shortage by building, and employee experience risk scores. Predictive Planning generates AI-powered executive summaries with each plan that show exactly where you have too much or too little space, what it's costing you, and what the ROI looks like for each option. Every number traces back to real behavioral data, not assumptions, so you can defend recommendations in leadership meetings.

Yes. Predictive Planning is built for enterprise-scale portfolios spanning hundreds of buildings across regions. The Large Spatial Model adjusts for regional work patterns, team composition differences, and local attendance behaviors. You can run scenarios at the portfolio level, like modeling the impact of consolidating three offices into one, or drill down to individual buildings and floors. For unmeasured sites, the model uses industry benchmarks to extend benchmarks across your entire portfolio from day one.

The Large Spatial Model (LSM) is VergeSense's AI foundational model, trained on eight years of real-world workplace data across 250+ million square feet. Unlike simple occupancy dashboards that report what happened yesterday, the LSM predicts how people will interact with space under different conditions. It generates "Usage Fingerprints," behavioral profiles that capture how an office actually works, and uses those to simulate realistic outcomes before you make any changes. It's the difference between planning on averages and planning on behavior.

Yes. VergeSense integrates with major IWMS systems to bring lease, asset, and reservation data into a unified view of your portfolio. You can also add your building's actual lease costs, annual lease cost, OPEX, lease length, and expiration date, directly in Predictive Planning's Building Settings. That cost data now surfaces alongside every forecast, so every scenario comparison carries real financial context, not just space and headcount numbers. The Large Spatial Model is also available via API for technology partners building planning, experience, or smart-building tools.

ROI varies by portfolio size and market, but the primary savings come from avoiding unnecessary lease renewals, consolidating underutilized space, and right-sizing before costly build-outs. Customers have used VergeSense data to uncover buildings running at 20% utilization and redirect that spend. Predictive Planning quantifies the financial impact of every scenario, so the business case is built into the output, not assembled after the fact.