By Meghan Hall
Modern offices have rapidly evolved as companies transitioned from traditional cubicles to open concept workspaces. VergeSense is a sensor-as-a-system platform that tracks office usage to equip companies with real time knowledge about how their offices are used. The Registry caught up with VergeSense’s Co-Founder and Chief Executive Officer, Dan Ryan, to see how the platform is impacting the way businesses use their spaces.
What inspired the creation of VergeSense? What was your role in creating the platform, and what is your role now that the platform is up and running?
I’ve been interested in IoT / Smart Buildings for basically my entire career — going back to when I was studying Electrical Engineering as an undergraduate at Boston University. While I was there, I spent some time at the Smart Lighting Engineering Research Center, which was conducting research in using LED lighting as a digital platform for delivering services, including things like sensing, indoor-wayfinding, asset tracking and wireless data communications. This led to me teaming up with one of my fellow colleagues to start my first company, ByteLight, which was the first company to deliver indoor-positioning via LED lighting.
We were acquired by Acuity Brands Lighting (largest LED Lighting company in the world), and that technology has now become an industry standard and is deployed across over 100 million square feet of space worldwide. I spent a few years at Acuity, where I ran the IoT product team and we diversified IoT / digital service offerings across a number of different vertical markets.
The two things that inspired the creation of VergeSense were part technology and part market. On the technology side, I’ve long been fascinated by the potential of computer vision sensors as a ubiquitous sensing platform, going back to my time as a student at BU. In fact, the original techniques we developed at ByteLight in the early 2010s leveraged vision sensors on smartphones to detect unique signatures that light broadcast. The challenge with computer-vision has been that the algorithms didn’t really start working until the more recent algorithms (using Convolutional Neural Networks) learning started taking off in 2011 and 2012.
The second piece of the equation is the massive shift underway in corporate and commercial real estate. As the next generation of workers come into the workforce, people are demanding a completely different type of workplace experience focused on agility and collaboration. The expectations of what workplaces look like are starting to change, and companies like WeWork are reinventing the concept of office space. And with this, real estate and property managers are demanding more data about the space is actually used — where people spend time, how conference rooms are actually used.
The VergeSense platform is based on inexpensive and easy to deploy sensors that measure anonymous data about occupancy in buildings. We’ve designed the product to be incredibly easy to install – literally one minute per device, which allows organizations to scale the solution across their properties with ease. And once they start to see the type of data our solution can generate, we’ve found that it becomes a new source of information that they can’t imagine operating without.
Where is VergeSense operating currently? Within specific geographical markets? Within certain companies?
We’re based out of the San Francisco Bay Area, but we have a distributed team with offices in Boston and a remote team in Europe. Most of our deployments are in the US, but we have recently started expanding into some select overseas markets in Europe and Asia. Right now, we have a one million square foot deployment footprint, which we expect to grow by 10 to 20 percent in 2019.
Who are the biggest users of VergeSense? Is the platform popular with that particular type of client or company?
To date, it has been large enterprises and property management firms. Our solution is certainly attractive to firms that measure their real estate assets in millions or even billions of square feet and need to maximize asset value. However, all types of real estate investors, property managers and workplace tenants looking to increase real estate asset values or develop more productive workplaces have expressed interest in our platform.
What is your sense of the commercial real estate market in major metros such as the San Francisco Bay Area and Puget Sound region? How do commercial real estate investors within those markets seek to benefit from the use of VergeSense?
As we’ve all seen, large increases in commercial real estate prices in the Bay Area have been a trend over the last few years and is one that we expect to continue. While areas like San Francisco and Puget Sound have seen significant rises, rising real estate prices and space efficiency is a problem that any organization with a physical presence is grappling with. Given San Francisco is also a technology-centric region, there is an openness to trying new technology that can better optimize what is becoming the biggest asset on the books of many companies.
The majority of organizations still want physical workspaces to attract talent, retain staff and provide collaborative and creative spaces to drive innovation. But while costs for space continue to rise, organizations are looking for ways to invest in great offices while reducing the skyrocketing overhead costs. And in truth, the majority of these office spaces are only 50 percent occupied.
But independent of the cost savings opportunities with space utilization, there are also employee experiential elements to the product, which are attractive across geographies. Examples include using sensors to identify available conference rooms, open desks to work at, or even telling you the estimated wait time in the cafeteria before you head to lunch.
Why does the commercial real estate market need a platform such as VergeSense? How does the technology use AI and machine-learning to process workspace utilization data?
Everyone in the commercial real estate industry is focused on how to provide a better experience within their properties. Without platforms like VergeSense you don’t have the data to understand the changes that are needed for a better experience.
Furthermore, first-generation sensors which didn’t have AI built into them provided the real-time data, but not the business recommendations based on that data.
That is the real leap forward with our sensor as a service platform. We’re not leaving real estate investors, property managers and workplace tenants awash in data with no idea what to do with it.
Our machine-learning modules work alongside our computer vision technology to process real-time workspace utilization data that recommends to building managers savings opportunities, better ways to allocate space and personnel within offices, and empowers a more enjoyable user experience.
How do experts in the commercial real estate market use this information to optimize the use of workspaces and office space?
They’re taking these recommendations and making changes to their workplaces in real-time. For example, VergeSense data can be streamed to a room booking solution to free up a conference room when no one shows up for a scheduled meeting.
VergeSense data can also power dynamic workplace strategies by identifying where employees are best situated to work at any specific moment. This opens up thousands of use cases for VergeSense data to accompany VergeSense applications currently in use across one million square feet of commercial properties. These applications are explained below.
What are some of the space recommendations that VergeSense gives to its users? Have these recommendations worked effectively when executed in physical offices spaces? Why or why not?
People Counting: Provides a real-time and historical count of the number of property occupants. Particularly important for conference rooms — we’ve seen data with some of our customers where conference rooms that are designed for upwards of 20 people never see a meeting size greater than four.
Room and Desk Utilization: Gives users the ability to measure utilization rates across a facility — from conference rooms to private offices, to co-working areas.
Hot Desking: Identifies open desks and dynamically assigns staff members to their desk to drive workplace efficiency.
Emergency Response: Pulls a count of every person in the building during an emergency event and their status.
In commercial real estate markets, layout trends such as open concept offices are becoming more common; what does VergeSense make of such office layouts? Does it find that open offices are efficiently used? Why or why not?
Our data is actually pretty clear — open offices deliver significantly higher space efficiency, upwards of 10 to 25 percent.
How do you think VergeSense will affect office layout and design in the future? Do you think technology will be the catalyst for a new type of office?
Historically, the design of an office space has been much more art than science. We have rough rules of thumb for the number of conference rooms and conference room sizes we need, how many desks to provide and what the ratios should be between fixed and flexed seating. The industry today is in a way still very much an analog space.
With the rise of sensors like ours and other analytical tools, we can help transform the future design of offices into a data-driven science and make sure we design buildings so that they respond and adapt to the needs of occupants.
Have you found that VergeSense has increased the value of properties? If so, by how much?
I’d say it’s pretty early to say, but what we have found is that our customers have a much more granular view of their spaces than ever possible before.
What does VergeSense hope to accomplish with the $1.5 million strategic investment led by JLL Spark? How will VergeSense expand its operations and improve its services with the funding?
We’re in growth mode right now. We’ve been generating revenue since very early on, and when the opportunity to partner with JLL Spark came up we were excited to welcome them, along with some of our other investors, Bolt and Pathbreaker. The main use of funds is focused on building our team so that we can continue to help our customers expand deployments faster and cover a wider footprint, and continue to build our analytics offering so that we can surface insights faster.
We have a hardware element to our offering so we’re also making investments in manufacturing capacity so that we can meet the demand.
We’re hiring so if any of this sounds interesting, send us a note to email@example.com.