Lambent SPACES

Manage Spaces Smarter

A New Way Forward

Organizations are currently experiencing an unprecedented shift in the way they use real estate, downsizing or hybridizing facilities to accommodate new modes of occupancy.

Yet they are still relying on old ways of managing space.

AI-powered Lambent Spaces lets you predict future spaces needs today.

WITHOUT NEW SENSORS

Lambent Spaces works with existing WiFi to get users up and running fast to enable:

One View For All Your Assets

MAPS

Log in to our MAPS feature anytime to see utilization rates across and entire corporate or college campus with a local or global view.

Automatic Utilization Reports

REPORTS

With a few simple steps, share monthly reports to internal stakeholders for greater collaboration and informing C-suite of critical data points.

Side-by-Side Comparisons

SCENARIO

Test various strategic space planning models by looking at predictive analytics for smarter space planning.

NO MORE WASTED SPACE

ANALYZE

Which spaces are approaching capacity? Which ones are collecting dust? You can see all relevant utilization data daily with an easy-to-understand interface.

SECURE, FLEXIBLE DEPLOYMENT

Lambent Spaces replaces inaccurate, manual counters and anecdotal reporting with an automated and AI-based system that integrates with existing WiFi. Supplementing with additional inputs, such as security cameras and RFID sensors, increases resolution in the spaces you’re monitoring. Flexible deployment options include on-premises, cloud, and edge devices, with various hybrid configurations available. In many cases, no additional hardware is required to implement our spatial analytics technology.

Data Sources

Backend Infrastructure

Services and Applications

PRIVACY IS PARAMOUNT

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HOW IT WORKS

First, data is collected from edge data sources. Proprietary algorithms and machine learning produce spatial estimates of occupancy, location, and movement.

Second, these estimates are streamed securely to an appliance in your data center — or a virtualized appliance for cloud-based deployments — where it is aggregated and anonymized.

Third, the data is sent to our cloud where our models analyze it and report back through the administrative dashboard.

OR IT COULD BE DISPLAYED LIKE THIS

STEP 1

First, data is collected from edge data sources. Proprietary algorithms and machine learning produce spatial estimates of occupancy, location, and movement.

STEP 2

Second, these estimates are streamed securely to an appliance in your data center — or a virtualized appliance for cloud-based deployments — where it is aggregated and anonymized.

STEP 3

Third, the data is sent to our cloud where our models analyze it and report back through the administrative dashboard.

FEATURED LAMBENT POSTS

Return to Office Means Rethinking Spaces

Corporations are facing the twofold challenge of having to reshape both physical offices and employee attitudes as they work to design return-to-office plans and satisfy a reluctant workforce. The challenge for the CRE industry is real – how to design for flexibility without adding more premium space that may sit unused most of the time.

The New Student Experience

Reduce deferred maintenance costs, make the most of every campus space and improve the overall student experience with deep insights for smart space planning. Aid Institutional Research Offices and solve interdepartmental space disputes with occupancy data.

ROI CALCULATOR

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LET DATA DRIVE DECISIONS

NEED FOOTER