TL;DR
- CVector addresses a key client concern: it pledges not to get acquired.
- Founders emphasize long-term commitment to critical infrastructure customers.
- Backed by Schematic Ventures with a $1.5M pre-seed round.
- Uses real-time data, open-source tech, and industry-specific insights.
- Operating across energy, chemicals, and manufacturing sectors.
Founders Prioritize Stability in a Volatile AI Market
As acquisition-hungry tech giants continue to absorb promising startups, CVector is differentiating itself by promising what many industrial customers want most: stability.
When meeting with utility providers, manufacturers, and energy firms, CVector’s founders — Richard Zhang and Tyler Ruggles — are repeatedly asked a pointed question: Will you still be around in a year? Their answer is unwavering: Yes.
“When we talk to these large infrastructure clients, 99% of the time this comes up within the first 10 minutes,” said Zhang in an interview with TechCrunch.
That assurance has already helped win over clients ranging from a California-based chemical manufacturer to national gas utilities, all of whom rely on CVector’s AI tools to streamline and optimize industrial operations.
Backed by Investors Who Understand Infrastructure
CVector’s anti-acquisition stance isn’t just rhetoric — it’s embedded into how they raised capital. Their recent $1.5 million pre-seed round was led by Schematic Ventures, an early-stage fund known for investing in industrial tech, supply chains, and infrastructure software.
“We wanted backers who understand hard problems in physical infrastructure,” Zhang said. “Schematic was the perfect fit.”
Julian Counihan, the Schematic partner who led the investment, pointed out that while some startups offer fail-safes like code escrow or perpetual software licenses in case of acquisition, customer trust still hinges on founder intent.
“It often comes down to whether the team is clearly mission-aligned,” Counihan told TechCrunch.
Built on Experience, Not Just Algorithms
CVector’s credibility doesn’t rest solely on its no-exit policy. Zhang and Ruggles bring high-impact backgrounds that align with the needs of their industrial clients.
- Zhang: Former software engineer at Shell, where he built apps for field operators unaccustomed to digital tools.
- Ruggles: PhD in experimental particle physics, with hands-on experience at the Large Hadron Collider, where he maintained uptime and analyzed nanosecond-scale data.
“That kind of operational background earns trust,” said Ruggles. “Our customers know we’ve been in high-stakes environments.”
Leveraging Unorthodox Tools to Build Industrial AI
CVector refers to its AI system as a “brain and nervous system for industrial assets.” Built with input from real-world operations, it integrates unconventional technologies and datasets to provide decision-making support for factories and energy networks.
This includes:
- Fintech APIs for real-time market data
- Energy pricing feeds for operational adjustments
- Open-source software from McLaren F1 to enhance precision timing and telemetry
“We don’t just analyze machine data,” Zhang noted. “We factor in the real world — like how snow and salt tracked into a factory can degrade sensitive equipment.”
Energy Sector Applications: Upgrading Without Replacing
One of CVector’s unique strengths is its ability to modernize aging infrastructure without full replacement. In the energy space, grid systems often rely on legacy codebases like Cobra or Fortran, making real-time management difficult.
CVector’s solution? Create low-latency AI overlays that sit atop old systems and enhance visibility and control.
“Operators don’t have to rebuild from scratch — they just get smarter tools,” Ruggles said.
CVector Snapshot: What Sets It Apart
| Feature | Details |
| Company Name | CVector |
| Funding | $1.5M pre-seed led by Schematic Ventures |
| Differentiator | Public commitment to avoiding acquisition |
| Key Clients | National gas utilities, chemical manufacturers |
| Sectors Deployed | Chemicals, energy, automotive |
| Founders’ Backgrounds | Shell (Zhang), Large Hadron Collider (Ruggles) |
| Unique Tech Stack | Fintech data, McLaren F1 open-source software, industrial AI overlays |
| Office Footprint | Providence, NYC, Frankfurt |
| Current Team Size | 8 people |
Scaling with Mission-Aligned Talent
With the close of the pre-seed round, CVector plans to grow—but not recklessly. Zhang emphasized that future hires will be “mission-aligned professionals” with a strong interest in long-term careers in infrastructure.
This deliberate approach to scaling ensures cultural fit and reinforces CVector’s core promise: We’re here to stay.
“Customers want confidence that you’re not building a demo,” Zhang said. “They want partners, not placeholders.”
A Startup That Moves Fast, But Stays Put
While Ruggles’ shift from particle physics to industrial AI might seem unconventional, he sees it as a welcome change.
“In academia, you wait for peer review and hope someone reads your paper,” he said. “Now I get to build tools that help factories run better, right now.”
That hands-on, collaborative ethos is central to how CVector operates — rapidly prototyping features with direct customer feedback and deploying real-world improvements without red tape.
