Doxel

AI teaching computers to make business sense of ill-lit 3D objects. We invested in Doxel, because of Saurabh Ladha, and his co-founder Robin Singh. They are without much parallel when it comes to the tech of 3D semantic understanding, and with their team of CS PhDs essentially writing software using AI to teach computers to make sense of the 3D world around them  — even when in less than ideal, real world sites that have little to no light. Both founders come with exceptionally strong engineering backgrounds, having met on the Dubai campus and then they split off to respectively Stanford and Ann Arbor Michigan for further education. This technology has broad application to industries of any kind wanting to know what’s going on on any physical project of theirs, be it construction, agriculture, shipping, manufacture and many more have been relegated to a 2D static world. The Doxel founders have deployed their solution to report progress and quality to managers, on multi-billion dollar projects, in real time with high accuracy and fully automated due to Doxel’s proprietary AI algorithms. This autonomy computer vision technology has so many applications in today’s business world of autonomy, where we simply do not know what’s going on in most of the physical layers of businesses, until it’s too late.

Construction budget overrun as target market. Their excellent and best in class tech background was only 1/3rd the reason for the excitement to lead the Seed round. The construction industry notoriously overruns budget by $100s of Millions and sometimes Billions. Among all the target industries they could pick, Doxel has decided to target what we found was a brilliant and estimated 10 Trillion dollar target market of the construction industry. They’re quickly delivering on very obvious and immediately attention grabbing goal: Have “the robots” tell management in the construction industry, with great accuracy and immediately where the project is beginning to run off the rails, and take action before the money is lost, rather than managers waiting weeks to get a report that they may not even know is correct or not.

Reducing friction to customers. The third reason we decided to invest was the unusual and convincing focus on real customers. It was very early days in the company’s life, but Saurabh flew down to a client on their construction site, right after the pitch to us, and Robin was already there, working directly with the client, with no friction, bringing the before unseen technology to the construction clients in direct collaboration with them. When we did our due diligence, their familiarity and intimacy with the clients, walking around on the construction site, clearly an embedded part of the team, was very convincing, and not something that’s easy to compete with, nor easy to teach to anyone else. It’s customer focused technology adoption straight from the founders. Writing the complex proprietary 3D algorithms direct on the customer construction site, while seeing data streaming in from cameras live in the 3D point cloud, beats sitting in a lab and coming up with theories about it.

Beyond basic computer vision, contextualizing shape, location and size. One of the things that has excited me on the investment since we invested has been Saurabh and Robin’s extreme dexterity and clarity in getting to what matters for customers, not trying to prove their original ideas right, but focused on the product result that amaze the customers. An example of that is how construction projects target learning data is a bunch of black indistinguishable objects on the construction site, that traditional computer vision would play back more or less incomprehensibly. Doxel has taken their 3D algorithms beyond contextualizing just objects based on color, but are now live on sites with contextual data of shape, location and size — live — giving construction project operators and management a live job site in their hands!!

As they have begun monetizing their exceptional technology, they are now building out the management team to scale.