Lyric is a Sunnyvale-based AI platform built for the people who actually run supply chains. Its Lyric Studio harmonizes data, algorithms, configurable workflows, and accelerated compute so that planners, engineers, and data scientists can model, test, and deploy decision intelligence apps - from demand forecasting and inventory to network design and transportation. Fortune 500 customers use it to compress months-long modeling cycles into days.
Sarang Jagdale is a PhD engineer turned supply chain AI co-founder who spent over two decades cracking some of the world's hardest logistics problems - from IBM's global consulting floors to the startup that eventually became Lyric. As Head of Decision Science at Lyric, he architects the algorithmic core of a platform now trusted by Coca-Cola, Google, and Mondelez to make their supply chains think for themselves. Lyric raised $43.5M in Series B funding in August 2025, bringing total funding to $67M.
Jinlin Wang arrived in the United States in 1996 with $50 in his pocket and a borrowed one-way ticket to pursue a PhD in electrical engineering. Three decades later, he is General Partner at Foothill Ventures, an early-stage fund that has backed seven seed-stage unicorns - five of them founded by Chinese immigrant engineers. Wang's career spans big tech (PeopleSoft, Oracle, Yahoo, Microsoft), startup founding (Auryc, acquired by Heap in 2022), and venture investing through three successive funds totaling over $311M. He holds 7 patents and a cross-disciplinary worldview shaped by Tsinghua University, the University of Connecticut, and Stanford - a combination that informs his conviction that the most interesting startups sit at the edges between fields.
Cameron R. Wolfe, Ph.D. is a Senior Research Scientist at Netflix's Globalization team and the author of Deep (Learning) Focus, a twice-weekly Substack newsletter with 60,000+ subscribers that translates cutting-edge ML research into approachable long-form essays. A Rice University computer science PhD, he has built a reputation as one of the clearest explainers of large language models, RLHF, and AI agents in the field, bridging academia and industry with methodical depth and intellectual generosity.