This article breaks down Predictive Planning, the first product in VergeSense’s new Decision Intelligence suite, and the most advanced way for real estate, workplace, and leaders to predict future space needs, test scenarios instantly, and make decisions grounded in AI instead of guesswork.
Predictive Planning represents a major shift in how workplace teams plan. It moves organizations from reactive, backward-looking analysis to proactive, simulation-driven planning that shows exactly when an office will hit its limits, why it will happen, and what to do next.
In this article, we’ll cover how Predictive Planning works through its three components:
If you missed the first article introducing Meridian and the evolution from Occupancy Intelligence to Decision Intelligence, you can catch up here.
Planning & Scenarios: Test Every “What If” in Minutes
Every workplace and real estate leader faces the same set of “what ifs”:
What if headcount grows by 20% next quarter? What if we exit a lease or close a floor? What if hybrid attendance drops or shifts by team?
Attempting to answer those questions traditionally required static spreadsheets, consultant studies, and manual modeling that took months. Predictive Planning changes that by creating a living model of your portfolio that updates in real time.
At its core, Planning & Scenarios defines a baseline plan (your current mix of supply, demand, and policies) and then allows you to run simulations to test proposed changes to see the impact on employees and your space . You can adjust any variable (headcount, attendance policy, new lease, design change) and immediately see how it impacts utilization, cost, and experience.
“The framework is built to simulate moments that haven’t happened yet,” explained Kelby Green, VergeSense CTO and Co-Founder. “We take your current context — floor design, measured occupancy, even team structure — and project it forward. What breaks first? What becomes a bottleneck? It’s a model of how your office actually behaves, not a static ratio.”
Each scenario visualizes future states, where capacity will peak, when comfort levels will be exceeded, and how employee experience will change as usage intensifies. Workplace, facilities, and operations leaders can compare options side-by-side, quantify ROI, and present plans to Finance in hours, not months, all with math that can be traced, explained, and trusted.
Supply: Find Your True Capacity Before You Hit a Wall
“A large spatial model works just like an LLM except instead of learning language, it learns usage,” said Kelby. “It takes your floor structure, teams, region, and any measured data, and generates a probability model of how your people will use that space. That’s what lets us simulate moments that haven’t happened yet.”
During VergeSenses’s AI for Smarter Real Estate & Workplace Decisions webinar, Kanav Dhir, VP of Product, emphasized the blind spot in traditional planning:
“You might think you can support 800 people because that’s what your design spreadsheet says, but realistically the office breaks at 400 because that’s when the conference rooms run out.”
Predictive Planning identifies this real-world threshold through breakpoints, the exact moment a critical space type is saturated. These breakpoints are discovered by simulating thousands of possible usage patterns, not guessing from averages.
Trained on 200M+ sq. ft. of measured workplace behavior, the LSM runs thousands of Monte Carlo–style simulation cycles to model the full range of how people might actually use a space. Instead of relying on a single average, it captures the real probabilities behind workplace behavior, accounting for:
For real estate, workplace, and facilities operations leaders, this means you finally know your building’s limits and how to fix them before they become problems.
Demand: Forecast What’s Coming Next
On the demand side, most workplace and real estate teams look at headcount, stated attendance policies, and rough adherence estimates to get a sense of demand. But these inputs are usually treated as static assumptions—a simple “expected attendance” number that rarely reflects how people actually behave or how patterns shift week to week. Without a way to model reality, those inputs can’t reliably show when demand will spike, how policies influence peak days, or when a floor will get overloaded.
Predictive Planning approaches the same inputs in a fundamentally different way. Instead of treating headcount, policy, and adherence as fixed numbers, the Demand engine turns them into behavior-driven forecasts. It models how those factors interact over time, how real employees actually come into the office, and most importantly how many people will be onsite at the same time, which is what truly determines space load.
“Adherence is the truth of your attendance,” Kanav explained. “Badge data tells you how many people actually come in, not how many are expected to. That adherence rate flows all the way through to the true peak number of people you need to plan for.”
This last point is crucial: peak attendance — not average attendance — is what breaks an office. Predictive Planning calculates it using real signals (badge, sensor, Wi-Fi) when available, or industry and regional benchmarks from the Large Spatial Model when they aren’t. That means even offices without measurement can generate credible demand forecasts, and those forecasts get more accurate as more real data comes online.
Kanav also noted that workplace leaders often underestimate how policy affects demand:
“If you change from three days a week to four days a week, that change propagates through the whole model. Suddenly your expected concurrent attendance looks very different, and you can see that instantly.”
Rather than treating policies as static ratios, Predictive Planning treats them as behavioral modifiers on the workforce, combining them with measured adherence patterns to forecast future demand with precision. Leaders can test:
And instantly see how each scenario impacts attendance peaks, and where demand will exceed supply.
The Impact: From Reactive to Predictive
For real estate, workplace, and facilities operations leaders, Predictive Planning changes planning from a backward-looking exercise into a forward-looking strategy.
Planning & Scenarios replaces guesswork with instant, side-by-side futures so leaders can see exactly how headcount changes, policy shifts, or lease decisions will impact space needs and employee experience.
Supply becomes grounded in reality, not ratios. Breakpoints reveal the true functional capacity of a space, powered by spatial simulations that show what will run out first and why — giving teams the insight to fix issues before employees feel them.
Demand becomes a dynamic forecast, driven by real attendance behavior, adherence patterns, and policy inputs. Leaders can anticipate peak loads and prepare for change instead of reacting to it.
Together, these components create a living model of the workplace that updates as the business evolves. Planning cycles shrink from months to hours. Business cases become measurable and defensible. And workplace teams can finally make decisions with confidence, not compromise.
→ See Predictive Planning in action. Schedule a demo here