Know the Stack Plan Works Before
Anyone Moves

Occupancy-based planning is the practice of deciding how much space you need, what type, and where, based on measured evidence of how spaces are used rather than headcount ratios or design capacity. A traditional plan assumes one desk per person and counts seats on a floor plan. Occupancy-based planning starts from what the data shows: how many people come in on a peak day, which space types run short, and where capacity sits unused.

Meridian supports this with forecasting and continuous measurement, so the plan recalculates when attendance, headcount, or policy changes instead of going stale between annual reviews.

No. Predictive Planning works with just a floor plan, as the Large Spatial Model predicts behavior using benchmarks drawn from 250M+ sq ft of real workplace data, giving you a defensible starting baseline on day one. Sensors, WiFi, videoconferencing, and badge data make the model more precise over time by shifting from modeled to measured precision, but they're an upgrade path you add when the decision calls for it, never a prerequisite to begin.

Consultants deliver a static report after 3–6 months, typically costing $250K–$1.5M per engagement, and it's often outdated before it arrives. VergeSense delivers a continuously updated planning engine instead: model unlimited scenarios, get instant answers, and update plans as conditions change without re-engaging anyone. Run it yourself, or you can work with VergeSense's Strategic Advisory Services team, included with every subscription, if your team doesn't have the bandwidth to run it internally.

The platform can ingest data from occupancy sensors (95%+ accuracy), WiFi infrastructure (up to 85% accuracy), badge systems, and booking platforms, and it automatically reconciles and de-duplicates signals across sources into a single occupancy model. For sites without any measurement in place, the Large Spatial Model uses industry benchmarks calibrated to your industry and building type to simulate realistic occupancy patterns until real data starts flowing in.

Yes. Scenario modeling lets you compare lease exits, renewals, consolidations, and expansions side by side, with predicted impact on capacity, employee experience, and cost. You can also add your building's actual lease costs, annual lease cost, OPEX, lease length, and expiration date, directly in Predictive Planning, so every scenario carries real financial context instead of relying on a separate spreadsheet to translate space decisions into dollars.

Predictive Planning uses Monte Carlo simulation, running 1,000+ scenarios per plan, to produce probabilistic forecasts with confidence intervals rather than a single-point guess. That means you see a realistic range of outcomes, not just one number to bet a lease decision on. When connected to live occupancy data from sensors, videoconfeencing systems, or WiFi, forecasts shift from modeled to measured precision and calibrate to your building's actual behavior over time.

AI-generated executive summaries showing capacity surplus or shortage by building, cost impact per scenario, payback timelines, and employee experience risk scores, all in language a finance audience can act on without translation. Every number traces back to real behavioral data rather than assumptions, so you can walk into a leadership meeting and defend the recommendation directly instead of building a separate business case to support it.

Yes. Predictive Planning adjusts for regional work patterns, team composition, and local attendance behavior, so a forecast for your Singapore office isn't built on the same assumptions as one for London. Run scenarios across hundreds of buildings at once, including unmeasured sites where you have no sensors or WiFi data yet, all from a single platform instead of stitching together separate regional reports.

Yes. VergeSense integrates with major IWMS platforms natively and is available via a fully documented API for anything not covered by an existing connector. Headcount feeds from HR systems to automatically update demand forecasts are on the product roadmap; today, you can incorporate headcount data manually to model reorg, growth, or team stack scenarios. Contact our team for the current integration list for your stack.

Seconds. Change an input, headcount, a policy shift, an attendance assumption, and the model recalculates instantly rather than requiring a new round of analysis. There are no spreadsheets to rebuild and no waiting on a consultant's next deliverable. This is what makes it possible to test five scenarios in a single meeting instead of committing to one plan based on a single static study.