Eclipse Capital has secured $1.3 billion in fresh funding to back physical AI startups working at the intersection of technology and the real world. The Palo Alto-based venture capital firm disclosed the fundraising through filings with the Securities and Exchange Commission. This latest capital haul represents the firm’s largest fund to date. It surpasses the $1.23 billion Eclipse raised back in 2023, according to Bloomberg reporting on the raise.
Founded in 2015 by Lior Susan, Eclipse has consistently directed resources toward physical AI startups that build technology for tangible industries. The firm’s total assets under management now sit at approximately $10 billion, as reported by The Next Web. Rather than chasing digital-only trends, Eclipse has doubled down on sectors like transportation, energy, infrastructure, and defense.
How Eclipse Plans to Deploy Capital for Physical AI Startups
The $1.3 billion fund is split into two distinct vehicles. Eclipse Fund VI holds $720 million for early-stage investments in physical AI startups. Meanwhile, the Early Growth Fund III contains $591 million to support companies approaching commercial scale. This dual structure lets Eclipse nurture ventures from inception through market readiness.
Partner Jiten Behl considers this moment the start of the next major technological wave. Over the past two decades, the industry saw waves driven by the internet, mobile cloud, and social media. Now, tangible breakthroughs in robotics and autonomous systems push AI beyond the screen. These advances are reaching factories, roads, and energy grids in ways that digital-only innovation never could.
Behl also emphasized that Eclipse maintains a substantial war chest. This financial strength allows the firm to make a significant impact throughout the full development journey of its physical AI startups portfolio. The scale of the fund positions Eclipse to lead larger funding rounds as companies mature.
Notable Portfolio Companies in the Physical AI Startups Space
A quick look at Eclipse’s recent investment history reveals clear conviction. The firm backed electric boat manufacturer Arc. It also invested in battery recycling innovator Redwood Materials, a company founded by former Tesla CTO JB Straubel. Redwood recently closed a $425 million Series E round that brought Google on board as a new investor.
Beyond clean energy, Eclipse placed bets on Bedrock Robotics. This autonomous construction vehicle startup raised over $270 million in Series B funding to develop AI retrofit kits for heavy machinery. The firm similarly invested in Wayve, a London-based autonomous driving company. Wayve recently secured $1.2 billion in Series D funding from Nvidia, Uber, and several major automakers. Industrial robotics pioneer Mind Robotics rounds out the portfolio with its focus on AI-enabled manufacturing automation. Mind Robotics closed a $500 million Series A round co-led by Accel and Andreessen Horowitz.
These investments highlight the growing momentum behind physical AI startups. Investor appetite for companies that merge intelligent software with real-world hardware continues to surge across the sector. Eclipse also sits on the board of AI chipmaker Cerebras Systems through founder Lior Susan. Cerebras is expected to pursue a public listing soon, further validating the broader physical AI thesis. The chip company has raised over $1 billion in recent rounds as enterprises seek alternatives to Nvidia for AI inference workloads. Susan’s board seat at Cerebras also gives Eclipse deep insight into the semiconductor landscape that powers autonomous systems.
Building an Ecosystem of Interconnected Physical AI Startups
While many firms are racing to invest in physical AI startups, Eclipse differentiates itself through its ecosystem approach. Instead of treating each portfolio company as an isolated bet, the firm fosters connections between startups in overlapping sectors. Behl explained that this strategy creates a powerful network effect.
Collaboration plays a central role in achieving scalability. By encouraging partnerships among physical AI startups early in their lifecycle, Eclipse helps them establish proof points. These proof points then attract additional market demand. The framework strengthens individual ventures while cultivating mutual support across the broader ecosystem. For instance, a battery technology company might partner with an autonomous vehicle developer. Together, they could create integrated solutions neither could build alone.
This interconnected approach also helps portfolio companies navigate the unique challenges of hardware development. Physical AI startups face longer development cycles than pure software ventures. They need manufacturing partnerships, supply chain management, and careful attention to unit economics. Eclipse’s ecosystem model addresses these hurdles by pooling resources and expertise.
Eclipse’s Incubation Strategy for New Physical AI Startups
Eclipse does not just fund external founders. The firm also intends to build companies from scratch within its own walls. Behl confirmed that the incubation initiative is already underway. Several concepts are in active development, with a focus on enterprises that transcend traditional sector boundaries.
This approach aligns with a broader trend in venture capital. Firms increasingly act as startup studios rather than passive investors. Eclipse’s operator-first identity supports this model well. The firm’s partners include former operators from Amazon, Apple, and Samsara. Their experience in manufacturing, supply chains, and scaling physical products gives Eclipse-backed founders a practical edge.
The incubation track also allows Eclipse to identify white space in the physical AI startups landscape. By spotting gaps where no suitable company yet exists, the firm can assemble founding teams and guide product direction from day one. This studio model helps reduce early-stage risk while capturing more upside. It also gives Eclipse a first-mover advantage in emerging categories before competitors can respond.
Data as the Competitive Moat for Physical AI Startups
As Eclipse looks toward the future, Behl raised essential questions about cross-sector data leverage. The firm believes that diverse sectors can achieve scalability by sharing operational data. Training AI models on information from transportation, energy, and defense simultaneously could yield benefits far beyond what any single-sector approach delivers.
This data-driven thesis represents Eclipse’s overarching strategy. Companies within the portfolio can use shared datasets to train smarter models. As TechCrunch noted in its coverage of the fund launch, Eclipse sees these ventures as key players bridging digital intelligence and real-world impact.
The timing coincides with record venture investment flowing into robotics, autonomous systems, and AI infrastructure throughout early 2026. Investors increasingly recognize that the most transformative AI applications will operate in the physical world. Eclipse’s $1.3 billion bet on physical AI startups signals that this shift from software to hardware-enabled intelligence is well underway.
The fund launch also arrives during a period of massive capital concentration in AI. Global venture funding reached $189 billion in February 2026 alone, with robotics and autonomous systems attracting a significant share. Physical AI startups are benefiting from this tailwind as hardware costs decline and AI models become more capable. Eclipse’s strategy of combining direct investment with incubation positions the firm to capture value at every stage of this transformation. For founders building at the frontier of physical AI startups, Eclipse now represents one of the most well-resourced partners available in the venture landscape.