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Real-time workspace analytics.
Data is the new gold, initially, the biggest data mining operations happened in the virtual world. Google data-mined the public web, Facebook data-mined your social network activity, and almost every software company imaginable followed suit. The same mechanics that make data-mining attractive also apply in the analogue world, hence the proliferation of different kinds of sensors in the built world.
Data is the new gold, and just like during any gold rush it’s great to sell shovels, or picks, or high-tech metal detectors. This week we will take a closer look at VergeSense, one of the leaders in producing the AI-powered sensing devices that allow the commercial real estate to unlock real-time occupancy data.
VergeSense offers a sensor-as-a-service platform, it combines motion sensors with computer vision components to enable accurate occupancy detection. It uses AI run on the sensors to distinguish between a vacant and a non-vacant workplace. More basic sensors only determine whether someone is sitting at a desk, but for instance, the VergeSense sensors can take into account personal belongings left at the desk as an indicator that the person will return to the same desk later on.
imagery courtesy VergeSense
VergeSense provides a utilization dashboard that helps companies recognize underutilized zones allowing them to optimize for better usage of the available space. They partner up with other proptech companies that leverage their sensor data into various use-cases range from workplace intelligence platforms, building automation systems, and desk booking software.
VergeSense was founded in 2017 by Dan Ryan and Kelby Green. They joined the prestigious Y combinator accelerator program that year. They secured more than $22.6M in funding en struck deals with enterprises like Shell, Roche and Cisco and strategic alliances with JLL, CBRE and Allegion.
🕵️♀️ Who else?
The workspace analytics marketplace is a wildly contested one, multiple well-funded startups are competing for a spot in your office building. Most offerings are clearly structured as a platform-play, they gather the necessary data and make it available through an API to 3rd party solution providers that build useful applications on top of the platform.
To keep the competitors list manageable we exclude the classic stick-to-the-desk occupancy sensor providers.
Pointgrab is an Israeli company providing the CogniPoint Sensing platform. It boosts very similar characteristics to the VergeSense solutions.
Density is another sensor-based occupancy analytics tool. They claim to be the most cost-effective system on the market because of the size of the area that one sensor can cover.
Basking is a German startup that uses your existing Wi-Fi hardware to provide live occupancy data. Leveraging your existing infrastructure is more cost-effective, but you sacrifice some accuracy without dedicated hardware.
Locatee is a Swiss company that also uses Wi-Fi installations, but also has the ability to motion sensors and other data-sources that might already be present in the building. They have the ambition to become the Google Analytics of office buildings.
CoWorkr leverages thermal sensing technology for its sensors, Their sensors can be battery operated which might be a plus when retrofitting. They provide a real-time API and workplace analytics dashboards.
Counterintuitively Covid-19 has been an opportunity for workspace analytics, obviously analyzing empty offices is not the use-case with the highest ROI, but occupancy analytics was quickly marketed as a tool that would enable the safe return to the office… This might be a big selling point in the short term, but even in a world without indoor capacity limitations workspace analytics still have considerable advantages.
The ability to recognize usage patterns and detect underused amenities is the most obvious one, but the partnership with external solution providers results in a breadth of possible use-cases. Some of the cases we found: Integration with facility management to improve maintenance and repair cycles, Integration with meeting room booking software to release unclaimed reservations, communicate crowds in the lunchroom, Improving discovery when hot-desking, … and many more could be conceived.
👎 Why not?
All forms of data-gathering come with certain privacy risks, even though most solutions claim to be designed with privacy safeguards in place (that’s one of the reasons why VergeSense runs the AI on the sensor devices and not in the cloud), the openness of the platforms could be abused by bad actors combining different datasets to pinpoint certain individuals or subgroups.
Starting with workplace analytics takes a certain amount of up-front investments both financially and in time commitment, so the implementation only makes sense when you have enough workspace under management to make sure the potential optimizations make sense in the context of your specific organization.
📚 Further reading?
Unlike this office space, we exclude the sensors based on finger movements because of practical reasons…