This industrial AI startup is winning over customers by saying it won’t get acquired

In a tech landscape increasingly dominated by major players aggressively acquiring promising AI startups, one industrial artificial intelligence firm, CVector, is charting an unconventional course to win over customers: a steadfast commitment to remain independent. This unique strategy directly addresses a prevalent concern among prospective clients in critical sectors, who frequently question the longevity of emerging tech partners.

The industrial AI sector, vital for optimizing manufacturing and utility operations, faces a peculiar challenge. With tech giants offering astronomical salaries and engaging in elaborate ‘acqui-hire’ deals, smaller, innovative startups often find themselves absorbed, leaving their clients uncertain about long-term support and continuity. This instability poses a significant risk, especially for critical infrastructure providers who rely on consistent, reliable technological partnerships.

CVector’s co-founders, Richard Zhang and Tyler Ruggles, have recognized this critical industry apprehension. When confronted with the inevitable question—”Will you still be here in six months? A year?”—their answer is resolute: CVector is here to stay. This assurance is proving to be a powerful differentiator, attracting a growing list of clients that includes national gas utilities and a prominent chemical manufacturer in California.

Richard Zhang emphasized the importance of this commitment, stating to TechCrunch, “When we talk to some of these big players in a critical infrastructure, the first call, 10 minutes in, like 99% of the time we’re gonna get that question. And they want real assurances, right?”

To further solidify their long-term vision, CVector strategically partnered with Schematic Ventures, which recently led a $1.5 million pre-seed funding round. Zhang highlighted the importance of aligning with investors known for tackling complex problems in supply chain, manufacturing, and software infrastructure—a core focus for Schematic Ventures.

Julian Counihan, a partner at Schematic Ventures, underscored the significance of founder commitment. He noted that beyond practical solutions like code escrow or perpetual software licenses in case of acquisition, “it comes down to founders being mission-aligned with the company and clearly communicating that long-term commitment to customers.”

CVector’s early success is a testament to this unwavering dedication. The founders bring a wealth of relevant experience: Zhang’s background includes software engineering for oil giant Shell, where he developed solutions for field operations, while Ruggles, with a PhD in experimental particle physics, honed his expertise in managing high-uptime, low-latency systems at the Large Hadron Collider. This blend of practical industrial insight and high-reliability system management instills confidence in their clients.

Beyond their impressive résumés, CVector, established in late 2024, has demonstrated remarkable ingenuity in developing its industrial AI software architecture—dubbed a “brain and nervous system for industrial assets.” Their innovative approach integrates diverse technologies, from fintech solutions and real-time energy pricing data to open-source software originally developed by the McLaren F1 racing team.

The company’s platform excels at incorporating nuanced, real-time data to optimize operations. Zhang provided an illustrative example: while weather conditions directly affect high-precision manufacturing, secondary effects, like salt carried into a factory on workers’ boots after snow, can also subtly impact sensitive equipment. CVector’s AI is designed to detect and account for such previously unexplainable variables, enhancing operational efficiency and profitability.

Tyler Ruggles highlighted the value of these insights: “Bringing those kinds of signals into your operations and your planning is incredibly valuable. All of this is to help run these facilities more successfully, more profitably.”

CVector has already successfully deployed its industrial AI agents across various sectors, including chemicals, automotive, and energy, with an ambitious eye on “large-scale critical infrastructure.” For energy providers, a common challenge involves grid dispatch systems built on archaic languages like Cobra and Fortran. CVector addresses this by creating advanced algorithms that overlay these legacy systems, providing operators with enhanced visibility and low-latency real-time management capabilities.

Currently, CVector operates with a lean, eight-person team distributed across Providence, Rhode Island; New York City; and Frankfurt, Germany. As their pre-seed funding empowers growth, the founders are meticulous about recruiting only “mission-aligned people” who genuinely aspire to build a career in physical infrastructure. This focused hiring strategy further reinforces their commitment to long-term stability and continued customer trust.

For Ruggles, the transition from theoretical physics to practical industrial application has been deeply rewarding. He expressed profound satisfaction in seeing direct, tangible impact: “I love the fact that instead of trying to write a paper, submit it, get it through the peer review process and get it published in a journal and hope that somebody looks at it, that I’m working with a client on something that’s in the ground and that we could be helping them keep it up and running. You can make changes, build up features, and build new stuff for your customers — rapidly.”