A family venture office.

Lew's prior ventures have focused on the emerging technologies of their time while navigating the volatility of the major tech cycles of the past 4 decades, from the rise of telecom and media, to personal computing and the internet, through the mobile and social media revolution, to today's era of cloud, artificial intelligence, and now Physical AI. Coupled with the period's major financial cycles, the dot com bubble, the 2008 global financial crisis, crypto booms, and periods of rapid expansion and volatility, Lew's journey reflects deep learnings of both tech transformation and economic forces shaping our world including the current prospect for circularity.

Lew started with early experience in environmental economics through degrees from Colorado College, and applied MBA skills with Price Waterhouse Consulting. Since those early structured days, he has founded and scaled over 20 startups including factories, developed satellite-based communication business, founded SaaS companies, some direct and others while running a family venture office. He has taken a startup public as founder and CFO (Nasdaq: INDE), started a venture fund and managed nearly all types of public and private financings and exit transactions.

QC3 Ventures is the culmination of applying all this experience with family both born and adopted to incubate and pursue the passion of a lifetime, physical AI and prospect for circularity it will inspire.

Jake's path to Physical AI began not in a lab or a startup, but in the field. Nearly a decade of hands-on environmental research, from conducting kelp forest surveys with PISCO across the Northern Channel Islands to managing ecological datasets for the Resilience Institute (RIBBiTR) and analyzing pelagic fisheries with the California Department of Fish and Wildlife, gave him a deep understanding of what environmental monitoring actually requires at the point of collection. That fieldwork revealed a fundamental gap: the boundary layer data that matters most for understanding ecosystems is the hardest to collect at scale.

Bridging that gap required building systems, not just collecting samples. Jake earned an M.S. in Data Science from UC Santa Barbara's Bren School and a B.S. in Environmental Studies, then moved into enterprise data engineering. As a Senior Business Intelligence Engineer at Alaska Airlines, he designs production-grade data pipelines using PySpark, Delta Tables, and Databricks Lakehouse, leading post-merger data integration following the Hawaiian Airlines acquisition. He specializes in medallion architecture (bronze to silver to gold), schema governance, and AI agent development for data automation, the same architectural patterns that now power TerraFirma's cloud data platform.

At QC3 Ventures, Jake serves as the technical bridge between environmental science and scalable AI systems. He leads TerraFirma's full technology stack, from edge AI on NVIDIA Jetson and autonomous flight systems to the Databricks cloud infrastructure that processes millions of observations into trustworthy environmental intelligence. His conviction is that the tools to understand our planet at the resolution it demands are finally within reach, and that building them is both the opportunity and the responsibility of this generation.

Joe's path to Physical AI started in the field, working directly with scientists and wildlife managers who needed better tools to infer the hard-to-measure processes that drive ecosystem change. Nearly a decade of work in wildlife ecology and statistics, from tracking golden eagles and Arctic caribou to studying sea otters and Pacific walrus, gave him a ground-level view of how difficult it is to turn raw environmental data into decisions.

That experience shaped his conviction that the next leap in environmental monitoring and management will come from tightly integrated hardware, software, and models that respect both the physics and the biology on the ground. Joe's technical foundation is built from a Ph.D. in Biological Sciences and an M.S. in Statistics from the University of Alaska Fairbanks with a B.A. in Biology from Colorado College.

His research has spanned movement and migration ecology, risk mapping, and population dynamics, with peer-reviewed work on a range of quantitative methods, including mechanistic movement models, ecological diffusion, and habitat selection applied to a range of species. In parallel, he has built open-source tools and visualization platforms that help translate telemetry and survey data into operational insight for practitioners who have to make calls under uncertainty, not in theory.

He is active in the broader scientific community, mentoring students and postdocs, holding leadership roles in professional societies, and receiving recognition from federal agencies for impact and early-career leadership. That background reflects a consistent focus on practical, mission-driven problems rather than purely academic ones. At QC3, his mix of field perspective, quantitative rigor, and tool-building informs how he evaluates opportunities and helps shape Physical AI solutions designed for complex environments.