Nvidia’s investment footprint across the artificial intelligence landscape has expanded considerably over the past two years, according to data compiled by PitchBook and reported by TechCrunch. The chipmaker participated in roughly 67 venture rounds in 2025, up from 54 in 2024 and just 12 in 2022. Its formal corporate venture arm, NVentures, completed 30 deals in 2025 alone. In total, Nvidia has invested approximately $53 billion across 170 deals spanning the entire AI ecosystem, per PitchBook figures cited in the source material.
The recipients of Nvidia’s capital read like a directory of every layer in the AI stack. Model builders include OpenAI, Anthropic, Mistral, xAI, Cohere, and Thinking Machines Lab. Infrastructure providers include CoreWeave, Nscale, and Nebius. Autonomous driving startup Wayve received backing, as did robotics firm Figure AI. Chip design tools company Synopsys received a $2 billion equity stake from Nvidia in December. Even quantum computing firm Quantinuum and nuclear fusion companies made the list.
Several individual deals exceeded $100 million, and the source material details five of them specifically.
In May 2024, Nvidia invested in a $140 million round for Weka, an AI-native data management platform. The round valued the Silicon Valley company at $1.6 billion.
In April 2024, Nvidia participated in Runway’s $308 million round, which was led by General Atlantic and valued the startup developing generative AI models for media production at $3.55 billion, according to PitchBook data. The chipmaker has been an investor in Runway since 2023.
In September 2024, Nvidia invested in Sakana AI, a Japan-based startup that trains low-cost generative AI models using small datasets. The startup raised a Series A round of about $214 million at a valuation of $1.5 billion. Sakana later raised another $135 million at a $2.65 billion valuation in November 2024, but Nvidia did not participate in that subsequent round.
In June 2024, autonomous trucking startup Waabi raised a $200 million Series B round co-led by existing investors Uber and Khosla Ventures. Other investors included Nvidia, Volvo Group Venture Capital, and Porsche Automobil Holding SE.
In December 2024, Nvidia invested in the $155 million round of Ayar Labs, a company developing optical interconnects to improve AI compute and power efficiency. This marked the third time Nvidia backed the startup.
Beyond these large deals, NVentures has also made strategic bets in newer areas. In 2025, the corporate VC fund backed Legora, a legal AI startup, marking Nvidia’s first legal AI investment. Legora is a Swedish-born legal tech startup that leverages AI to help lawyers streamline their work, and it competes with U.S. player Harvey. The company’s marketing campaign features actor Jude Law.
Nvidia’s investment strategy appears to involve hedging its bets across competing startups. The source material notes that Nvidia invested in both Anthropic and OpenAI before deciding it has “probably had enough” in that particular segment.
The source material also references remarks from Nvidia CEO Jensen Huang at the Cisco AI Summit, reported by Fortune on February 4, 2026, where he discussed letting “a thousand flowers bloom” and commented on return on investment. Additional coverage from SiliconANGLE on February 5, 2026, noted Huang’s remarks on an abundance mindset, 1,000 internal AI projects, and innovation. A transcript from the Cisco AI Summit, published by SingjuPost on February 7, 2026, included Huang on reinventing computing and the Cisco partnership.
Why it matters for European robot service
For European companies operating in the robot service sector, Nvidia’s sprawling investment portfolio signals several trends worth watching.
First, the scale of Nvidia’s commitments — roughly $53 billion across 170 deals — indicates that the company is not merely selling chips but actively shaping the ecosystem that will consume those chips. This matters for robot service providers because the hardware and software stack they rely on is increasingly influenced by Nvidia’s strategic choices. When Nvidia invests in infrastructure providers like CoreWeave, Nscale, and Nebius, it is effectively subsidizing the compute capacity that AI-powered robot services will depend on. European operators should consider whether these investments will lead to more competitive pricing for cloud-based AI processing, or whether they will consolidate market power in ways that affect procurement decisions.
Second, the investment in Ayar Labs, which develops optical interconnects to improve AI compute and power efficiency, is directly relevant to robot service operators who deploy edge computing or on-premises AI processing. Optical interconnects are a foundational technology for data center networking, and Nvidia’s repeated backing of this startup — three times, per the source material — suggests the company views power efficiency as a critical constraint for future AI workloads. European robot service providers that operate fleets of autonomous machines, particularly in logistics or manufacturing, will need to track how these efficiency gains translate into the hardware they deploy. The source material does not disclose specific performance metrics or deployment timelines for Ayar Labs’ technology, so operators should be cautious about assuming near-term availability.
Third, the investment in Waabi, an autonomous trucking startup, has direct implications for European freight and logistics. While Waabi’s operations are primarily North American, the technology stack — including simulation, sensor fusion, and decision-making algorithms — is likely to influence autonomous vehicle development globally. European trucking companies and robot service providers in the logistics sector should monitor whether Waabi’s technology is licensed or adapted for European road conditions, which differ significantly from North American highways in terms of regulations, infrastructure, and traffic patterns. The source material does not specify any European expansion plans for Waabi, so this remains an open question.
Fourth, Nvidia’s investment in Sakana AI, which trains low-cost generative AI models using small datasets, is relevant for European robot service providers concerned about the cost of AI model training. If Sakana’s approach proves scalable, it could reduce the barrier to entry for smaller European companies that want to develop specialized AI models for robot control, perception, or decision-making without massive compute budgets. The source material notes that Nvidia did not participate in Sakana’s subsequent $135 million round in November 2024, which could indicate a strategic reassessment or simply a preference for earlier-stage involvement. European operators should not read too much into this absence without additional information.
Fifth, the investment in Legora, Nvidia’s first legal AI investment, signals that the company is expanding beyond core AI infrastructure into vertical applications. For European robot service providers, this could indicate a broader trend: Nvidia may increasingly invest in application-layer startups that use its chips and software frameworks. This could create both opportunities and competitive pressures. On one hand, it might lead to better-integrated solutions for specific verticals. On the other hand, it could mean that Nvidia-backed startups in the robot service space will have preferential access to hardware, software, and capital. European operators should be aware that Nvidia’s investment strategy is not limited to infrastructure but extends to end-user applications.
Finally, the overall pace of Nvidia’s venture activity — 67 deals in 2025, up from 54 in 2024 and 12 in 2022 — suggests that the company is accelerating its ecosystem-building efforts. For European robot service providers, this means that the competitive landscape is likely to shift as Nvidia-backed startups gain market traction. The source material does not provide a complete list of all 170 deals, so there may be additional investments in European companies that are not disclosed in the cited reporting. Operators should consider whether Nvidia’s portfolio includes any direct competitors or partners in their specific market segments.
What buyers and operators should know
For buyers and operators of robot services in Europe, the source material offers several practical takeaways, along with some important caveats about what is not disclosed.
First, Nvidia’s investment in Weka, an AI-native data management platform, points to the growing importance of data infrastructure in AI-powered robot services. Weka’s $140 million round in May 2024, which valued the company at $1.6 billion, suggests that data management is considered a critical bottleneck for AI workloads. Robot service operators who handle large volumes of sensor data, telemetry, or training datasets should evaluate whether their current data management solutions are adequate for AI-driven workflows. The source material does not specify Weka’s pricing, performance benchmarks, or European availability, so operators should conduct their own due diligence before considering adoption.
Second, Runway’s $308 million round in April 2024, led by General Atlantic and valuing the company at $3.55 billion, indicates significant investor confidence in generative AI for media production. While this may seem tangential to robot services, the underlying technology — generating realistic video and imagery — has applications in robot simulation, operator training, and customer demonstrations. European operators who use simulation environments for testing robot behavior should monitor whether Runway’s models become integrated into simulation platforms. The source material does not disclose Runway’s roadmap or any European partnerships.
Third, Sakana AI’s approach to training low-cost generative AI models using small datasets is directly relevant to cost-conscious operators. The startup’s $214 million Series A round in September 2024 at a $1.5 billion valuation, followed by a $135 million round at a $2.65 billion valuation in November 2024, suggests strong investor interest in efficient AI training methods. However, the source material notes that Nvidia did not participate in the November round, which could indicate that Nvidia’s interest is limited to earlier stages or that the company has other priorities. Operators should treat Sakana’s technology as promising but unproven at scale, and the source material does not provide any performance data or deployment case studies.
Fourth, Waabi’s $200 million Series B round in June 2024, co-led by Uber and Khosla Ventures with participation from Nvidia, Volvo Group Venture Capital, and Porsche Automobil Holding SE, is a strong signal for autonomous trucking. The involvement of Volvo Group Venture Capital is particularly relevant for European operators, as it suggests potential pathways for technology transfer to European commercial vehicles. However, the source material does not specify any European deployment plans, regulatory approvals, or commercial partnerships for Waabi. Operators should not assume that Waabi’s technology will be available in Europe in the near term.
Fifth, Ayar Labs’ $155 million round in December 2024, which marked Nvidia’s third investment in the company, underscores the importance of optical interconnects for AI compute efficiency. For operators who run AI workloads in data centers or edge facilities, improvements in interconnect technology could reduce power consumption and latency. However, the source material does not provide any technical specifications, product availability dates, or pricing information for Ayar Labs’ solutions. Operators should treat this as a long-term infrastructure trend rather than an immediate procurement consideration.
Sixth, the Legora investment — Nvidia’s first in legal AI — highlights that Nvidia is willing to invest in vertical applications beyond its core hardware and software stack. For robot service operators, this could mean that Nvidia will increasingly back startups that use its platforms in specific industries, including potentially robotics. The source material does not disclose the size of the Legora investment or the valuation at which it was made, so it is difficult to assess the strategic significance. Operators should monitor whether Nvidia makes similar investments in European robot service companies.
Seventh, the overall scale of Nvidia’s investments — $53 billion across 170 deals — should give operators confidence that the AI ecosystem will continue to receive substantial capital infusions. This could translate into more capable, more affordable AI-powered robot services over time. However, it also means that the competitive landscape is likely to become more crowded, with Nvidia-backed startups potentially enjoying advantages in access to hardware, software, and capital. European operators should factor this into their procurement and partnership strategies.
It is important to note what the source material does not disclose. The reporting does not provide a complete list of all 170 deals, so there may be additional investments in European companies or in robot-specific startups that are not mentioned. The source material does not disclose any financial terms for the Legora investment, nor does it provide performance data for any of the mentioned startups. It does not specify any European regulatory implications, tax considerations, or export controls related to Nvidia’s investments. It does not provide any information about Nvidia’s networking business beyond a general description of technologies like NVLink, InfiniBand switches, Spectrum-X, and co-packaged optics switches. The source material does not disclose any specific SLA numbers, response times, or spare-part lead times for any products or services mentioned.
The source material also references remarks by Nvidia CEO Jensen Huang at the Cisco AI Summit, reported in early February 2026, where he discussed letting “a thousand flowers bloom” and an abundance mindset, as well as 1,000 internal AI projects. These comments suggest that Nvidia’s investment strategy is part of a broader philosophy of fostering widespread innovation rather than concentrating on a few winners. For European operators, this could mean that Nvidia is open to supporting a diverse range of startups, including those in the robot service space. However, the source material does not provide the full text of Huang’s remarks, so the context and specifics of these comments are not fully available.
In summary, Nvidia’s investment activity across 2024 and 2025 demonstrates a comprehensive strategy to build out the entire AI ecosystem, from model builders to infrastructure providers to vertical applications. For European robot service buyers and operators, the key takeaways are: data infrastructure is becoming more important, efficient AI training methods are gaining traction, autonomous trucking is attracting significant capital, optical interconnects are a long-term efficiency trend, and Nvidia is willing to invest in vertical applications. At the same time, many details remain undisclosed, and operators should conduct their own research before making procurement or partnership decisions based on these investments.
Sources
https://techcrunch.com/2025/10/12/nvidias-ai-empire-a-look-at-its-top-startup-investments/
Published by Vigla Media OÜ (Estonia).