WHO WE ARE
Founded in 2017, Lexset is dedicated to changing the world for the better by creating data and systems that enable Artificial Intelligence to understand physical spaces. When computers comprehend an environment, those environments become safer; our businesses become more productive and efficient; and we as humans make better decisions. As a result, we get to focus on solving complex and interesting problems, forming better relationships, and having more fun.
Founder and CEO
Francis works at Lexset’s HQ in Brooklyn, NY.
Francis is an early pioneer of Generative Design, the use of computational techniques to find new solutions to design and engineering problems. He is the author of “3D Printing Design: Additive Manufacturing and the Materials Revolution.” In his spare time, you find Francis on the golf course or using AI to generate art. Francis received his BFA in Computer Graphics from Long Island University and his M.Arch from Pratt Institute.
Founder & COO
Azam works at Lexset in Seattle, WA.
Azam is passionate about the role data plays in the creation of new technology. He has deep expertise on issues of data rights, IP, and business dev & ops. He is the former director of new ventures at Intellectual Ventures and former Dep. CoS of the USPTO. Azam is a father, husband, music-lover, skier, avid reader, and friend. Azam received his BA from Boston University and Juris Doctor from Depaul University.
Lead AI Engineer
3D Graphics Engineer
Generative AI Advisor
Home and Office Interior
We build robust interior home and office environments to train Computer Vision systems for anything from robotics navigation to Augmented Reality gaming.
Satellite and Drone Footage
We build data sets for satellite and drone applications capable of tracking humans, vehicles, or even spotting changes in landscape.
Warehouse and Factory
We build simulated warehouse and factory environments to increase efficiency and identify safety hazards for supply chain, retail, and advanced manufacturing.
Construction and Industrial Parts
We build simulated objects and environments to train for recognition and measurement of parts, removing the complexities of tracking and increasing quality assurance.
Please fill in this questionnaire to start your synthetic data journey