The AI startup frenzy is anything but hype. In the first half of 2025, global investments in AI startups reached more than $205 billionaccording to Crunchbase, with $145 billion raised in North America alone. And while observers may dispute their long-term viability, no one disputes the seemingly endless tsunami of new companies entering the fray. Some estimates put the number of AI startups worldwide at more than 10,000, with more than 5,000 emanating from the United States.
All this activity only adds to the pressure on venture capitalists trying to determine which companies have the technology and teams to develop and commercialize the next big thing. But for investment groups focused on a small but growing market segment – industrial AI – the stakes are even higher.
Unlike “traditional” AI which may take the form of a human resources chatbot or a marketing forecasting dashboard, industrial AI is the application of models and automation in critical systems in energy, transportation, manufacturing, finance, healthcare, and more. Issues common to enterprise AI, such as hallucinations, drift, bias, etc., are not tolerated in industrial AI. As such, selecting the right startups to invest with in this crazy environment is difficult.
“The fervor and volatility of the AI startup landscape is truly a perfect storm for venture capitalists,” says Gayathri Radhakrishnan, a partner at Hitachi’s investment arm, Hitachi Ventures. “You start by applying the myriad concerns you have with all startups, like cash flow, company structure, vision, team composition, intellectual property, etc. Simultaneously, you have to consider the chaos swirling around AI. And then, above all, you have to take the industry perspective and ask yourself: Can these guys succeed?”
For Hitachi Ventures, which invests in companies across the technology spectrum, AI due diligence requires a focused view on the sector that best fits its business.
What an investment in industrial AI looks like
This may be easier said than done, however. The explosion of AI startups has created challenges reminiscent of the cloud computing hype cycle of the early 2010s. “When the cloud became popular, every company claimed to be a cloud company,” says Radhakrishnan. “Today, every company claims to be an AI company. We need to cut through the noise to understand whether AI is core to their mission or just a feature.”
In 2023, the challenge of selecting AI investments has only intensified as capital flows into general-purpose foundation models, like ChatGPT. “The space was very crowded and even early Series A rounds were getting quite expensive,” she says.
Seeking a promising but less saturated niche that best fits Hitachi’s heritage in operational technology (OT) and information technology (IT), as well as its deep expertise in AI, Hitachi Ventures turned its attention to AI for industrial and physical environments.
Gain originality in modeling
One of his first investments was Archetype AI Inc., a Palo Alto startup building a foundational AI model that interprets sensor data – including sound, vibration, temperature and pressure – to perceive, understand and reason about the physical world. The company’s ultimate goal is to encode the entire physical world, which would allow it to predict equipment failures, optimize industrial processes and create digital twins of real-world operations.
Hitachi backed Archetype in December 2023, just seven months after the startup was incorporated – an unusually early stage for a venture capital investment – and well before physical AI began to become a mainstream investment. Archetype AI’s boundary-pushing nature makes it both promising and risky, a common balancing act for industrial AI investors.
“What Archetype is doing is clearly part of our thesis, but no one else was doing what they were doing at that time,” says Radhakrishnan. “We were a little uncomfortable about that, but we were also comfortable being uncomfortable. Sometimes the investments that could be the big winners don’t have precedent.”
As a corporate venture capital fund, with Hitachi as sole sponsor, Hitachi Ventures pursues a dual objective. “Our first responsibility is to generate strong returns,” says Radhakrishnan. “But we also want to create a broad strategic advantage for Hitachi. »
This means that the company’s extensive research into emerging technology areas serves multiple purposes, including identifying investment opportunities while informing the entire Hitachi organization about market trends. “Startups are often early indicators of technology waves,” she notes. “It is a beacon that illuminates what is happening in the distance.”
Achieving cognitive resonance
Hitachi Ventures’ investment in Xaba Inc.., illustrates this dual approach. The Toronto startup develops cognitive control systems for robotics, allowing machines to intelligently react to their environment in real time. Traditional robots are pre-programmed for specific tasks; if they encounter an obstacle, they either stop or cross it. Xaba’s xCognition technology, which combines physics-based modeling and AI learning, allows robots to perceive obstacles and automatically adjust their trajectory, essentially acting as a “brain” for the robot. This allows the robot to reason, adapt and generalize across tasks.
What convinced Radhakrishnan was not just the technology, but also the depth of the Xaba founder’s expertise, one of the many nuances that go into financing decisions. “Venture capitalists are jacks of all trades who know everything, but only know it deeply,” she says. “The founder has strong technical experience combined with industry knowledge, and he understands his field very well. »
When Radhakrishnan presented xCognition technology to his counterparts at Hitachi Rail Ltd., they immediately saw its value. The Hitachi subsidiary, present in more than 50 countries, is now deploying Xaba robots for precision machining on locomotive surfaces. These tasks require sub-millimeter precision that previously required significant manual labor.
But the Xaba team didn’t stop there. As AI co-pilots are all the rage for coding, Xaba has developed an automated programmable logic controller (PLC) code generator, called PLCfy, that helps democratize industrial automation. PLCfy provides an integrated AI layer that complements existing APIs with modern capabilities, such as predictive control, anomaly detection, and adaptive optimization, without ripping or replacing hardware.
The other side of consensus
Yet while Xaba seems like the ideal investment for Hitachi Ventures, it also demonstrates how complex the field of industrial AI is: Initially, partners on the company’s investment committee disagreed on whether it was worth pursuing.
“Sometimes when you can’t get consensus, those are deals where you think, ‘Maybe there’s something in there,'” she says. “Who would have thought that an online company selling books would redefine the world’s computing needs? Or that a social media company connecting friends would impact enterprise storage purchasing behavior? If the impact of an AI startup is obvious to everyone, you probably aren’t investing in the next Google, Amazon, or Facebook.”
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Gayatri Radhakrishnan is a partner at Hitachi Ventures. With over $1 billion in assets under management, the firm sets new standards for business, fostering partnership and access to ambitious founders who are transforming the world around us. From advanced AI and robotics to sustainable energy solutions and beyond, Hitachi Ventures sees the potential to invest in companies that dare to dream big and disrupt the status quo. The company’s expertise, combined with Hitachi’s global resources and commitment to innovation, enables it to identify and nurture promising startups with the potential to make a significant impact and shape the future of technology.
To learn more, visit Hitachi Enterprises.