Every Lease Decision, Backed by Evidence
Renewals and exits, consolidations, headcount shifts, and the operating cost of every building you hold. Model the decision in minutes, and walk into the room with numbers finance will accept.
Trusted by Real Estate Teams Managing
Large Global Portfolios
250M+ sq ft of real workplace DATA powering smarter portfolio decisions
THE PROBLEM
The Numbers You Have Aren't the Numbers You Need
Badge data tells you who entered the building, not how space was actually used. You’re making million-dollar lease decisions on a proxy metric that misses 30–40% of real activity.
Every site is measured differently, or not at all. You can't rank buildings against each other, so the underused ones stay invisible until a lease event forces the question.
Consultant studies cost $250K–$1.5M per engagement and deliver a static PDF that’s outdated before you open it. When headcount changes or policy shifts, you’re back to square one.
You’re defending recommendations with gut feel. The CFO wants numbers. The CHRO wants experience guarantees. You’re caught between cost pressure and employee satisfaction with no data to bridge the gap.
Three Steps to a Number You Can Defend
Model Any Scenario in Minutes
Upload a floor plan and your building data. Meridian, backed by 250M+ sq ft of real workplace behavior, shows you exactly how your portfolio will perform under any scenario, from lease changes to headcount shifts to policy updates, before you commit budget.
Ground Every Forecast
in Real Behavior
Connect badge, WiFi, booking, videoconferencing, or sensor data and predictions move from modeled estimates to measured precision. Every source you add sharpens the next decision.
Present CFO-Ready
Recommendations
with Conviction
Executive summaries quantify savings, payback period, and experience trade-offs, generated from the same model that produced the plan. The number in your board deck and the number in the analysis are the same number.
Built for Real Estate Teams Who Need
Answers, Not Dashboards
Portfolio-Wide Scenario Modeling
Model lease renewals, consolidations, and expansions across every site you hold. Change headcount, hybrid policy, or floor plan layout and see the impact on cost, capacity, and experience in seconds.
Demand Forecasting & Capacity Risk Analysis
See exactly when and where employee experience degrades as attendance patterns shift. The model identifies the specific space types that bottleneck first and the attendance threshold where problems begin.
Forecast Before You Changes
Upload a floor plan and your workforce context. The Large Spatial Model applies behavioral benchmarks from 250M+ sq ft to forecast how your space will perform, with no sensors and no installation project.
What Real Estate Leaders are Achieving with VergeSense
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in lease avoidance
HQ footprint reduction
annual savings per satellite office
Why Spreadsheets and
Consultants Can't Keep Up
Modern ways of working demand a modern approach to real estate planning.
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Frequently Asked Questions
What is occupancy intelligence for real estate?
Occupancy intelligence is the continuous measurement and analysis of how people actually use physical space, not a one-time snapshot. For real estate leaders, it replaces assumptions and proxy metrics with behavioral data from sensors, Wi-Fi, and booking systems, giving you the ground truth needed for portfolio decisions. Instead of estimating utilization from headcount, you see exactly how each building, floor, and space type is being used, day by day.
How does VergeSense help reduce lease costs?
VergeSense identifies underutilized space across your portfolio by measuring actual usage patterns, not reported occupancy or assumed headcount ratios. Predictive Planning then models consolidation and right-sizing scenarios with projected cost savings, capacity impact, and experience risk for each option, enabling real estate teams to avoid unnecessary lease renewals and optimize their footprint before signing anything, rather than discovering the wrong call was made after the lease is already in place.
How accurate is VergeSense occupancy data?
The Infinity sensor delivers 95% accuracy with AI-enabled passive occupancy detection, capturing space that's claimed by belongings even when no one is actively present. Wi-Fi-based measurement achieves up to 85% accuracy with automatic device de-duplication, useful for building and floor-level counts. Predictive Planning forecasts go a step further, including confidence intervals generated by 1,000+ Monte Carlo simulations, so you see a realistic range of outcomes rather than a single-point estimate.
Can VergeSense model headcount changes and policy shifts?
Yes. Predictive Planning lets you adjust headcount projections, hybrid work policies, attendance assumptions, and floor plan layouts, then instantly see the impact on capacity, employee experience, and cost across your entire portfolio. You can compare multiple scenarios side by side, for example a return-to-office mandate versus a continued hybrid policy, and see which one actually holds up against your real space and behavioral data before committing to either.
How long does implementation take?
For Predictive Planning, you can run your first scenario within days of uploading floor plans and workforce data, with no hardware deployment required to get started. Full occupancy intelligence deployments with sensors typically complete within 4–6 weeks, depending on portfolio size and system complexity. Either way, VergeSense's implementation team works directly with your team throughout, so you're not left configuring the platform on your own.
What ROI can real estate teams expect?
Real estate teams using VergeSense have avoided significant lease costs. Fresenius Medical Care, for example, achieved $6M a year in lease avoidance, $60M over 10 years, with no impact to employee experience. The platform replaces consultant engagements costing $250K–$1.5M each, and one avoided bad lease decision typically exceeds the annual subscription cost outright, which is why most customers see the platform pay for itself well before renewal.
How does Predictive Planning work?
Predictive Planning is powered by the Large Spatial Model, trained on 250M+ sq ft of real workplace behavior across industries and geographies. Upload a floor plan and workforce assumptions, and the model runs 1,000+ probabilistic simulations to forecast how your space will perform under any scenario, with or without sensors. As real occupancy data becomes available, forecasts shift from modeled to measured precision for even sharper accuracy.
Does VergeSense integrate with IWMS platforms?
Yes. VergeSense integrates natively with major IWMS and workplace platforms including ServiceNow, Eptura, FM Systems, and more, so lease, asset, and reservation data flows directly into your occupancy model. Open APIs enable custom integrations with any system in your real estate tech stack that isn't covered by a native connector, and most integrations are live within days rather than requiring a lengthy implementation project.
Is occupancy data GDPR and privacy compliant?
Yes. VergeSense is GDPR compliant and SOC 2 Type II certified. Sensors detect occupancy, not identity or any personally identifiable information, with no way to tie a data point back to an individual. All data is encrypted in transit and at rest, so real estate and legal teams can deploy occupancy intelligence at scale without introducing new privacy risk to the organization.
Can VergeSense ingest badge data?
Yes. Badge access data is a supported input alongside sensors, Wi-Fi, videoconferencing, and booking systems, giving you entry and exit patterns by location without requiring any new hardware. On its own, badge data only tells you who entered a building, not how space was used once they were inside, and it carries real accuracy gaps from tailgating and forgotten badges. Combined with VergeSense's other sources, it strengthens your occupancy baseline rather than standing in for space-level measurement on its own.
See What Your Workplace is Telling You
Get a walkthrough built around your buildings. We'll show you how they compare to 250M+ sq ft of real workplace data, and where the savings are hiding.