BusinessNewswireStartupsTechnology

Wave Function Ventures Raises $15M for Deep Tech Fund

▼ Summary

– Jamie Gull chose to work at Scaled Composites after graduating to quickly build and own outcomes rather than join a traditional aerospace company.
– He later contributed to SpaceX’s development of the reusable Falcon 9 rocket, a key milestone for the company.
– Gull has launched Wave Function Ventures, a deep tech fund that recently closed its first $15.1 million fund and plans to invest in 25 startups.
– His background includes angel investing, co-founding an eVTOL startup, and serving as a venture partner, which he leverages to support founders in deep tech.
– Gull believes deep tech offers significant long-term returns due to its ability to establish strong competitive advantages through non-venture funding.

Wave Function Ventures has successfully secured $15.1 million for its inaugural deep technology fund, marking a significant step for founder Jamie Gull as he transitions from a celebrated engineering career into venture capital. The fund will concentrate on early-stage investments in pioneering sectors such as nuclear energy, advanced robotics, and aerospace.

Jamie Gull’s professional journey began shortly after earning a master’s in aeronautics from Stanford in 2007. Rather than pursuing a conventional aerospace role, he headed straight for the Mojave Desert, drawn by Scaled Composites and its reputation for rapid, hands-on aircraft development. Gull recalls fearing he might spend half a decade “working on a latch” at a larger corporation, whereas at Scaled Composites he could immediately own meaningful outcomes.

After two years, Gull joined SpaceX, contributing directly to the reusability of the Falcon 9 rocket, a foundational achievement for the company. Now, he is channeling that experience into Wave Function Ventures, where he has already completed nine investments in startups including Deep Fission, Persona AI, and Airship Industries. The fund plans to make roughly 25 seed or pre-seed investments, backed primarily by high-net-worth individuals along with support from family offices and other funds.

Deep tech investing is gaining momentum, fueled by growing interest in aerospace, defense, and advanced hardware. This trend is reflected in other recent funds, such as Leitmotif, which launched earlier this year with $300 million from Volkswagen Group to support hardware and manufacturing startups in the U.S. and Europe.

Gull’s background extends beyond engineering. In 2016, he began angel investing in companies like Boom Supersonic, K2 Space, and Varda. He later co-founded Talyn Air, an electric vertical takeoff and landing startup that went through Y Combinator and was eventually acquired in 2023. Gull also serves as a venture partner at YC’s Pioneer Fund, a role he continues today.

He believes his multifaceted experience, spanning rapid prototyping, founding a company, and angel investing, positions him to assist founders during the most uncertain early phases. Gull is convinced that deep tech will produce substantial returns over the next 10 to 20 years, noting that although these startups often require significant upfront capital, they can tap non-venture funding sources like government contracts or asset-backed loans to build durable competitive advantages.

Patience is a theme Gull embraces. Early in his career, he contributed to Stratolaunch, then the world’s largest aircraft, a project so complex it remained in development long after he had moved on. A decade later, while preparing to attend a fly-in event at Mojave airport with his Talyn co-founder Evan Mucasey, Gull received a cryptic suggestion to arrive at 6 a.m. Upon approaching the airport, they saw Stratolaunch on the runway, poised for flight. Minutes later, it took off, a moment Gull describes as “wild,” reflecting both the long timelines and profound rewards inherent in deep tech innovation.

(Source: TechCrunch)

Topics

aerospace engineering 95% deep tech 90% venture capital 88% startup funding 85% space exploration 82% angel investing 80% nuclear energy 75% humanoid robotics 75% rapid prototyping 72% y combinator 70%