Eclipse’s $1.3B Fund: Why Physical AI Demands Builders, Not Just Check-Writers

$1.3 Billion for AI That Moves Things

Eclipse Ventures announced a $1.3 billion fundraise on April 7, 2026, split across two vehicles: Fund VI, a $720 million early-stage fund, and Early Growth Fund III, a $591 million vehicle for companies approaching commercial scale. It is the largest single fundraise in the firm’s 11-year history, following a $1.23 billion raise in 2023.

The capital is dedicated to what Eclipse calls “physical AI”: startups that merge artificial intelligence with robotics, autonomous systems, manufacturing hardware, and physical infrastructure. While most AI venture capital chases software-only companies building chatbots, copilots, and SaaS tools, Eclipse is focused on the messier, capital-intensive world where AI must operate in physical environments.

Founded in 2015 by Lior Susan, a former Flex executive, and legendary venture capitalist Pierre Lamond, Eclipse has built its reputation by backing companies at the intersection of software intelligence and industrial hardware. Its portfolio includes Cerebras, the AI chipmaker; Arc, which builds electric boats; Redwood Materials, the battery recycling company; Wayve, the autonomous vehicle technology developer; and Bedrock Robotics, which automates construction equipment.

The Builder Model: VCs Who Found Companies

What distinguishes Eclipse from traditional venture firms is its “buildco” approach. Rather than waiting for founders to pitch, Eclipse identifies gaps in the physical AI landscape, assembles founding teams, defines early product direction, and takes ownership stakes before any external investor sees a cap table.

This model debuted in 2018 with Bright Machines, Eclipse’s first company built from scratch. The firm assembled a team of industry veterans, defined the product vision for intelligent factory automation, and incubated the company before spinning it out. Bright Machines has since grown into a significant player in automated manufacturing.

The approach reflects a structural reality of physical AI: unlike pure software companies, hardware-AI startups need deep domain expertise in manufacturing, supply chains, and regulatory compliance from day one. A founding team of machine learning researchers alone cannot build an autonomous construction robot; they need mechanical engineers, supply chain operators, and regulatory specialists working alongside them from the first prototype.

Eclipse’s $720 million early-stage fund will fuel both traditional investments and new company creation, while the $591 million growth fund targets portfolio companies reaching commercial scale. This dual structure lets the firm support companies from inception through scaling.

The Ecosystem Strategy

Eclipse has also developed a deliberate ecosystem strategy where portfolio companies become partners. Startups in adjacent fields, like an AI chip company and a robotics manufacturer, can integrate their technologies and serve as reference customers for each other, building the proof points that enterprise buyers need before committing to new vendors.

This network effect is particularly valuable in defense and energy, sectors where new vendors face long sales cycles and intense scrutiny. A robotics startup backed by Eclipse can point to another Eclipse portfolio company as a satisfied customer, compressing the trust-building timeline that typically takes years in these conservative industries.

The sectors Eclipse targets, transportation, energy, infrastructure, compute, and defense, share a common characteristic: they are all critical to national economies but have been underserved by traditional venture capital. Most VCs avoid hardware-heavy companies because of their higher capital requirements, longer development cycles, and lower margin profiles compared to pure software. Eclipse’s thesis is that AI changes this equation by dramatically improving the economics of physical-world companies.

Physical AI’s Moment

Eclipse’s fundraise reflects broader market momentum in physical AI. Global spending on industrial robotics surpassed $16 billion in 2025, autonomous vehicle technology continues to attract billions in investment, and defense departments worldwide are accelerating procurement of AI-enabled systems.

The challenge for physical AI startups is that building hardware is fundamentally harder than building software. You cannot iterate a robot as quickly as you can push a code update. Manufacturing defects are costlier than software bugs. And regulatory approval for autonomous systems in defense, healthcare, or transportation takes years, not months.

Eclipse’s bet is that the venture-building model, providing not just capital but operational expertise, manufacturing partnerships, and sector knowledge, is what physical AI companies need to survive the “valley of death” between prototype and production. With $1.3 billion committed and a track record that includes Cerebras and Bright Machines, the firm is making its largest wager yet that AI’s next act plays out in the physical world.

Sources & Further Reading

• Eclipse Has a New $1.3B Fund for Physical AI Startups — TechCrunch
• Cerebras Backer Eclipse Raises $1.3B for Robotics, AI Infrastructure — Bloomberg
• Eclipse Crosses $1.3B Into Venture Building — The Meridiem
• Eclipse Ventures Raises $1.3B — Ventureburn
• Eclipse Ventures Launches $1.3B Fund — MLQ.ai
• Wayve, Cerebras Backer Eclipse Secures $1.3B — TechFundingNews