12.5.22-Paris-Lamarr.ai

JOHN E. FERNANDEZ: Very nice to be with you. So I'm presenting my company, when the slides come up. Lamarr.ai, and can we have it on these screens as well, or one of these screens? No? OK, Lamarr.ai, an autonomous solution for rapid building envelope diagnostics using aerial robotics and cloud computing.

Clicker not working, and I am definitely pressing the right button.

SPEAKER 1: The technology ends at 5:00.

[LAUGHTER]

JOHN E. FERNANDEZ: Well, should have told me beforehand. Clicker not working. Well, I could tell you about my company.

SPEAKER 1: It's working.

JOHN E. FERNANDEZ: OK, OK, great. OK, so very quickly, we know very well the challenge of the century is climate change. The built environment is a major contributor. We also know that the IPCC has designated the built environment, buildings and cities, as the smartest dollar you can spend to reduce energy consumption and greenhouse gas emissions.

Today in the United States, there are 10 million commercial and multifamily residential buildings. And they are now being regulated under more stringent energy and carbon emissions codes. So 61% of all construction today are projects in retrofitting, increasing, improving the efficiency of the exterior envelope of those buildings. So the active envelope retrofit industry, we suspect, will grow tremendously, maybe even doubling in a year or two.

Also 50% of US buildings have been built before 1980. Before 1980, and those buildings are rapidly aging, so that 40% of energy losses are from the envelope, an enormous percentage of energy losses from the built environment. Today the auditing process of exterior envelopes is done almost completely manually, through site visits and interviews, equipment, expensive equipment, and then reports are put together by building scientists, building experts.

The available envelope analytics and audit process is therefore not easily scalable, not scalable really in any good way. So we founded Lamarr.ai on the basis of research funded by the US Department of Energy. It's the tool that we have produced, the product, is like giving the building envelope an MRI scan to autonomously detect thermal defects in the exterior envelope.

It is an integrated autonomous solution for rapid building envelope diagnosis, which includes the data collection itself, the use of computer vision to identify and then to analyze those thermal anomalies, and then inputting those into a 3D model, a digital twin, that then produces an energy model. So the company provides any one of these, or a subset of these, or all of them, flight planning, data collection, image processing, automated image processing based on a machine learning model, geometry construction using RGB images and photogrammetry, and energy modeling.

By way of thermal images, as I said, we have a machine learning model that identifies and then classifies those thermal anomalies and then places them on the photogrammetry-produced 3D model. Those anomalies in yellow that you see there are tagged. They're identified and they then lead to the building energy model.

Today our algorithm sits in the cloud. And a user uploads those images. The analysis, we can analyze 1,000 images in under one second to give you the identification and the classification, and then the user can click on those anomalies to then decide how to repair, how to respond to that thermal anomaly in the building. Our technology saves 85% in time, 90% in cost, and is safer and more accurate because you don't have people at the site climbing buildings or on scaffolding, with a handheld thermal camera.

The three elements of the service that we provide generally, aerial data, thermal inspection, and energy modeling, are serviced by these companies. And we know all of these companies very well. But we're the only company that provides broadly all of these services in an automated package. So we are essentially a software as service company.

The market is about $150 billion globally, $41 billion for US retrofit, and $22 billion the envelope retrofit market. In particular, our beachhead markets are in New York and Boston, although our contracts now are national in the United States. Our two revenue streams, the first product is for large building operators, owners, and managers to upload data, have it diagnosed, and then to repair. And our second market, which we will start in about a year or so, is the homeowner, who also captures images using a smart camera, a thermal camera on a smartphone, uploading images, and then we diagnose. And they then do their own repair.

It's a completely scalable solution. And in fact, we are already exceeding the number of units that we've analyzed that's shown on this curve. And the team that we've put together bridges the core competencies needed, from building science to robotics, machine learning, and computer vision. These are my colleagues at Georgia Tech, my PhD student and now postdoc, and then a professor at Syracuse University.

So OK, so just an explanation on the name. We are dedicating the name of our company to Hedy Lamarr, inventor of signal hopping technology, which is used originally in radio and now in Wi-Fi technologies, and to all innovators who did not gain prominence for their inventions during their lifetime, especially women. So we are Lamarr, an integrated autonomous solution for building envelope diagnosis without the audit headache. Thank you.

[APPLAUSE]