The venture capital landscape is undergoing a palpable shift as the frenzy around pure‑play software begins to ebb, and money starts flowing toward the tangible foundations of the economy. A pair of former Apple executives has seized this moment, launching a $33 million fund dedicated to early‑stage companies that bring artificial intelligence, sensors and robotics onto the factory floor. Rather than betting on the next chatbot or SaaS platform, Simon Lancaster and Sabrina Paseman argue that the real multiplier for AI lies in the physical world where goods are designed, assembled and shipped. Their thesis rests on the observation that every high‑value industry—semiconductors, defense, aerospace, pharmaceuticals and energy—depends on a shared manufacturing technology stack. By improving that stack with smarter software, connected hardware and intelligent automation, they believe they can unlock productivity gains that ripple outward across global supply chains. The timing is critical: labor shortages are pushing manufacturers to seek automation, geopolitical tensions are encouraging reshoring, and the cost of essential components such as microcontrollers and vision systems has fallen dramatically. In this environment, a focused fund that can marry deep process expertise with early‑stage capital is uniquely positioned to identify and nurture the next generation of industrial innovators.
Lancaster and Paseman bring a rare blend of product‑development credibility and hands‑on manufacturing experience to the venture world. During their tenure at Apple, Lancaster spent over a decade guiding complex hardware projects from initial concept through pilot runs to mass production, gaining an intimate understanding of how design decisions translate into yield, cost and scalability challenges on the shop floor. Paseman, after six years at the same company, focused on consumer‑facing devices and later pivoted to a personal project aimed at improving the fit of surgical masks—a venture that gave her direct exposure to material sourcing, prototyping and regulatory hurdles. When they both departed Apple in the same month of 2019, it was not a coincidence but a convergent moment that allowed them to reflect on where the next big technological leap might occur. Their post‑Apple paths further reinforced this view: Lancaster helped scale a robotics startup, wrestling with the realities of integrating motion control, machine vision and safety standards into a viable product, while Paseman’s mask‑seal project taught her how subtle material changes can have outsized impacts on usability and compliance. Together, these experiences convinced them that the most pressing inefficiencies in modern industry are not hidden in lines of code but in the physical processes that turn raw materials into finished goods.
At the heart of Omni Ventures’ thesis is the concept of a unified digitization stack that underpins disparate sectors. This stack comprises layers of software for design simulation and production planning, sensors that capture real‑time data from machines and workpieces, connectivity fabrics that move that information to the cloud or edge, analytics engines that turn raw data into actionable insights, and actuation systems—robots, collaborative arms, automated guided vehicles—that execute decisions on the floor. When any of these layers is upgraded, the benefits propagate: better simulation reduces scrap, smarter sensing cuts downtime, tighter connectivity enables predictive maintenance, and more dexterous automation raises throughput. Because the same architectural blocks appear in a semiconductor fab, a pharmaceutical filling line, an aerospace assembly cell and an energy‑equipment plant, improvements in one domain often transfer readily to another. Omni’s founders argue that investing in startups that innovate anywhere within this stack yields outsized leverage, as a single breakthrough—say, a new AI‑based vision algorithm—can be adopted by machine shops, automotive suppliers and medical‑device makers alike. This cross‑pollination potential differentiates manufacturing‑focused venture from more siloed software bets, where a successful product may only serve a narrow niche.
Several macro‑economic and technological forces are converging to make the current moment ripe for a manufacturing‑tech renaissance. First, artificial intelligence has migrated from conversational agents confined to screens to embodied systems that perceive, reason and act in three‑dimensional space—a shift championed by Nvidia’s Jensen Huang under the banner of ‘physical AI.’ Second, the bill‑of‑materials cost for essential hardware such as lidar, high‑resolution cameras, edge AI processors and flexible robotic arms has declined steeply over the past five years, lowering the barrier to entry for automation projects. Third, persistent labor shortages in developed economies—exacerbated by aging workforces and shifting immigration patterns—are pushing manufacturers to seek solutions that augment or collaborate with human workers. Fourth, geopolitical tensions, especially the push to reshore critical supply chains away from single‑source dependencies, are prompting governments and corporations alike to incentivize domestic production capabilities. Finally, the software investment boom, which saw record‑breaking valuations for SaaS and consumer apps, has begun to cool as investors seek more defensible, revenue‑generating models with tangible assets. Together, these trends create a fertile environment for early‑stage ventures that can deliver measurable productivity gains, cost reductions and resilience improvements to industrial customers.
The data backs up the narrative of rising capital interest in the physical side of AI. According to PitchBook, global venture capital invested in robotics and physical AI companies expanded from roughly $4 billion in 2019 to an estimated $26 billion by the close of 2025—a more than sixfold increase in just six years. In the first half of 2025 alone, companies operating in this space have already secured over $23 billion, indicating that the momentum shows no sign of slowing. This surge is not limited to a single geography; funding rounds are appearing in the United States, Europe, East Asia and increasingly in emerging industrial hubs such as Mexico and Vietnam, where multinational firms are setting up new production lines. Notable sub‑sectors attracting capital include autonomous mobile robots for warehouse logistics, AI‑driven quality‑inspection systems for precision machining, collaborative robotic arms for electronics assembly, and digital‑twin platforms that simulate entire factories before a single piece of metal is cut. The breadth of activity suggests that investors are viewing manufacturing‑tech not as a niche curiosity but as a horizontal enabler that can boost productivity across the entire industrial base. For a fund like Omni Ventures, which targets pre‑seed companies with checks ranging from $700 k to $1 m, this macro‑level inflow translates into a healthier follow‑on ecosystem, where early successes can attract Series A and B rounds from larger, sector‑agnostic VCs.
Omni Ventures has structured its fund to make a meaningful impact at the earliest stages of a company’s life cycle, where strategic guidance and modest capital can de‑risk technology development and accelerate product‑market fit. The fund plans to write checks between $700 k and $1 million into pre‑seed manufacturing‑tech startups, a range that is large enough to support prototype builds, initial hiring and early customer pilots, yet small enough to allow the fund to diversify across a portfolio of roughly 30‑40 companies over its lifetime. Geographic focus is primarily the United States, where the founders see the strongest combination of engineering talent, venture infrastructure and policy incentives for reshoring, but they remain open to backing founders elsewhere whose technologies have clear applicability to global supply chains. Sector agnosticism is a core tenet: rather than concentrating on a single vertical such as automotive or aerospace, Omni looks for innovations that touch the shared digitization stack—software platforms that streamline quoting for machine shops, sensor suites that enable predictive maintenance on CNC machines, or AI orchestration layers that coordinate fleets of autonomous guided vehicles in a warehouse. By maintaining this breadth, the fund aims to capture the cross‑industry spillover effects that amplify the value of any single technological advance, while also reducing reliance on the fortunes of any one market.
To illustrate the type of ventures Omni is backing, the fund has already placed capital in three distinct but thematically aligned startups. Uptool offers an AI‑powered quoting platform designed specifically for small and medium‑sized machine shops that traditionally rely on manual spreadsheets and delayed email exchanges to generate job estimates. By ingesting CAD files, analyzing feature complexity and referencing real‑time machine‑hour rates, Uptool can produce accurate, competitive quotes in minutes, helping shops win more work and improve capacity utilization. Cargo Robotics addresses the intra‑factory logistics challenge of moving heavy pallets and components between workstations; its modular robotic carts combine lidar‑based navigation, swappable payloads and a fleet‑management software layer that lets operators schedule and monitor deliveries via a simple tablet interface. Dystr, meanwhile, provides an AI‑driven engineering assistant that helps mechanical, electrical and hardware engineers navigate complex design rules, standards libraries and simulation tools, effectively reducing the time spent on repetitive checks and freeing engineers to focus on creative problem‑solving. Each of these companies exemplifies the fund’s emphasis on solving concrete pain points that practitioners encounter daily, while also leveraging widely applicable technologies such as computer vision, natural‑language processing and edge computing. The presence of follow‑on investors like Khosla Ventures, Eclipse, Kleiner Perkins and Bessemer Venture Partners in some of these rounds further validates the market’s confidence in the underlying concepts.
The involvement of established venture firms in Omni’s portfolio companies serves as an important signal that the manufacturing‑tech thesis is gaining traction beyond a handful of specialized angels. When Khosla Ventures, a fund known for backing breakthroughs in sustainability and frontier technologies, decides to co‑invest in a machine‑shop quoting tool, it suggests that they see a scalable, recurring‑revenue model rooted in industrial efficiency. Eclipse Ventures, which focuses on deep‑tech and industrial automation, bringing its expertise in scaling robotics firms, adds credibility to Cargo Robotics’ go‑to‑market strategy. Kleiner Perkins’ participation points to a belief that the AI orchestration layer Dystr offers can become a horizontal platform akin to GitHub for hardware engineers, with network effects that improve as more users contribute data and models. Bessemer Venture Partners, with its strong track record in enterprise SaaS, recognizing value in a tool that streamlines engineering workflows, underscores the crossover appeal of manufacturing‑focused software that mimics the usability and adoption patterns of more familiar office applications. This blend of specialist and generalist investors indicates that the market is beginning to view manufacturing innovation not as a speculative side bet but as a core component of a diversified, future‑proof portfolio. For Omni, such validation eases the path to raising follow‑on capital for its own portfolio companies and reinforces the fund’s own thesis that the digitization stack is a horizontal lever with wide‑reaching impact.
The journey to convince limited partners that manufacturing deserved a dedicated venture fund was not always smooth. Just three years ago, when Lancaster and Paseman were first shaping their investment thesis, the prevailing sentiment among many VC partners was that the manufacturing sector was too fragmented, too capital‑intensive and too slow‑moving to generate the outsized returns typical of software‑centric funds. Comments such as ‘This is cool, but it’s a little niche, guys’ were common in early conversations, reflecting a perception that the addressable market for factory‑floor AI was limited to a handful of large OEMs. However, the macro shifts described earlier—labor constraints, geopolitical re‑shoring, falling hardware costs and the emergence of physical AI—have rapidly altered that calculus. Today, the same investors who once questioned the viability of manufacturing‑tech are now eagerly asking how they can gain exposure to the trend, with some even repositioning their own funds to capture a share of the burgeoning robotics and automation landscape. The change in attitude underscores a broader realization: the factories that produce everything from smartphones to lifesaving drugs are themselves becoming software‑defined, and the winners in the next decade will be those who can master the intersection of code, hardware and process knowledge. Omni’s founders take pride in having persisted through the skepticism, using their own operational experience to demonstrate that real problems exist and are ripe for entrepreneurial solutions.
The name Omni Ventures was chosen deliberately to embody the fund’s all‑encompassing view of manufacturing’s role in the modern economy. ‘Omni’ signals that the firm sees manufacturing as a ubiquitous layer that touches virtually every product and service we rely on, from the smartphone in our pocket to the turbine generating electricity for a city. As Lancaster explains, the moniker serves as a constant reminder that every object in the world is manufactured, and therefore improvements to the manufacturing process have cascading effects across countless verticals. This perspective aligns closely with the idea of ‘global dynamism,’ a term the founders use to describe a worldwide version of the ‘American Dynamism’ framework popularized by Andreessen Horowitz. While American Dynamism focuses on investing in companies that bolster national interests in areas such as aerospace, defense, manufacturing and critical infrastructure, global dynamism expands the lens to include the international supply chains, emerging manufacturing hubs and cross‑border technology flows that define today’s economy. By investing in startups that enhance the digitization stack, Omni aims to contribute to a more resilient, efficient and innovative global industrial base—one that can adapt quickly to shifts in demand, geopolitical pressures and technological change, ultimately strengthening the competitiveness of nations that embrace these advancements.
When evaluating potential investments, Omni looks for founders who possess a rare combination of deep technical credibility and commercial intuition, typically forged through five to fifteen years of hands‑on experience in manufacturing environments. The partners believe that the most compelling ideas arise from individuals who have personally felt the friction of inefficient processes—whether it is the tedium of manually generating quotes for a machine shop, the frustration of unexpected downtime caused by a poorly maintained conveyor, or the complexity of navigating ever‑changing regulatory standards for medical device production. Such founders are not only capable of building a prototype that works in a lab, but they also understand the practical constraints of integrating new technology into an existing production line, from change‑over time and worker training to safety certifications and supply‑chain considerations. By backing entrepreneurs who are solving problems they themselves have encountered, Omni gains confidence that there is a genuine product‑market fit, reducing the risk of building a solution in search of a problem. Furthermore, these founder‑led teams tend to retain a strong operational mindset as they scale, which helps preserve the close connection between product development and customer needs that is essential for industrial technologies where adoption cycles longer and trust is earned slowly over months or years of proven reliability on the shop floor.
For readers looking to act on the insights from this story, there are several concrete steps depending on your role. If you are an early‑stage investor or limited partner, consider allocating a modest portion of your portfolio to specialized manufacturing‑tech funds or directly to pre‑seed startups that demonstrate clear ROI metrics such as reduced scrap rates, increased OEE (overall equipment effectiveness) or lowered labor intensity. Look for teams with founders who have lived the problem they are solving and who can articulate a path to revenue within 18‑24 months. If you are an entrepreneur with a background in engineering, operations or industrial automation, identify a pain point you have witnessed repeatedly on the factory floor, validate it with at least three potential customers before writing a line of code, and seek out advisors who have both deep technical knowledge and experience scaling industrial hardware. For policymakers and economic development officials, the data suggests that supporting education programs that blend traditional trade skills with AI, robotics and data literacy can create a workforce ready to operate the next generation of smart factories. Finally, for established manufacturers, piloting one of the emerging solutions—whether an AI quoting tool, a collaborative robot or a predictive‑maintenance sensor—can provide quick wins that build internal confidence for broader digital transformation initiatives. By taking these steps, stakeholders can help accelerate the shift from software‑only innovation to a balanced ecosystem where the physical and digital realms advance together.