Chris is the visionary & tenacious leader of L&A, his third start-up in the AgTech space. He previously founded Robodondo, which was acquired by Motivo Engineering in 2017, then built & rapidly grew Motivo’s B2B AgTech business into their primary vertical and led early market research for the technology that would become Monarch Tractor. Chris left Motivo in 2019 to cofound Stout Industrial Technologies, establishing their core technical team, strategic industry partnerships, intellectual property, and overseeing the completion of the initial series development of the Stout Smart Cultivator before continuing his relentless pursuit of creative destruction with his most capable team yet.
Chris Laudando
Founder/President
Carl is L&A’s “controller of the future”, with a tenured Big Four consulting pedigree that has provided him with a depth & breadth of audit, management consulting, advisory, and tax services experience. He is an award-winning team leader, having received industry recognition at Deloitte and Kaiser Permanente where he worked prior to joining L&A. Carl obsesses the minutiae and thrives in high pressure environments where he genuinely finds joy navigating the fiduciary responsibilities attached to serving the largest, most complex public & private companies in the world.
Carl T. Schroedl
CPA Controller
Steve is a unique talent, serving as L&A’s primary operations lead & client relationship manager. He is a veteran of complex hardware development & Silicon Valley program management, having led nearly a dozen AgTech developments over the past 6 years. A pilot and certified airplane mechanic, Steve’s career began in aerospace, where engineering paradigms differ from the “traditional” development views found in agriculture. His cultural connection to growers and veteran AgTech development experience brings tremendous value to L&A clients - especially those embarking on their first ever tech development journey with L&A.
Steve Babin
Director of Operations
Tim is L&A’s methodical and detail-oriented design engineer. He has professional mechanical, design, and product engineering experience that spans from CAT to Stout to Meta. Tim’s design work reflects the engineering ethos of L&A, that an automatic machine be made elegant by way of maximized simplicity. He is a perpetual student of engineering and incessantly pursues the betterment of all that surrounds him.
Tim Doctor
Principal Design Engineer
Hari relocated from Brooklyn to join L&A after receiving his postgraduate degree from NYU’s Control/Robotics Research Laboratory (CRRL) in May of 2023. He is passionate about machine perception, autonomy, and challenging the CTO to apply the latest emerging technologies to L&A automation systems, especially if it results in the most robust solution. His specialties include monocular SLAM, real-time (ML/non-ML) multi-instance object detection & tracking, sensor fusion, and neural radiance fields (NeRF).
Jagennath Hari
Embedded Systems Engineer
Hunter is L&A’s field operations lead. Born to a ranching family from Hollister, CA, Hunter has had a lifetime front row seat to the challenges facing specialty crop growers in CA. Not surprisingly, he has been working to be part of the solution for his entire career – which has included operations roles at Farmwise, Naio Technologies, and Nexus Robotics. Hunter’s industry knowledge & hard-built relationships are part of the magic that allows L&A bridge the cultural gap between high tech and “get r’ done”.
Hunter Torres
AgTech Operations
Kyle’s depth & breadth of technical ability, and his incessant desire to continue building upon that multi-domain knowledge, made him perfect for the lead technician role at L&A. He is an extremely rare talent that can conceptualize, ideate, design, fabricate, weld, build, print, solder, wire, assemble, et al. His professionalism, eternal optimism, and calm & collected disposition is very well suited to the challenging work we do – and makes him a favorite with L&A clients.
Kyle Wells
Lead Technician
Ilya is L&A’s principal ML engineer and data scientist. He studied Soil Science at Lomonosov Moscow State University, Russia and published statistical analysis/models that predict methane flow and the genotoxic effects of heavy metals on plant cells in vitro. In 2017, he began exclusively researching machine learning for agriculture automation, working to optimize plant growth in greenhouses and enrolling in a Ph.D. program at the Center for Data Intensive Studies and Engineering at Skoltech, Russia (MIT) where he concentrated on stochastic optimization techniques, deep learning tools for computer vision, and reinforcement learning – all modern tools he leverages to solve age old problems in agriculture.