AI infrastructure startup Infinity has raised $15 million at a $100 million valuation to build software that automatically creates the low-level code AI chips need to run inference — the process of using a trained model to generate predictions or output. The round includes Touring Capital, Principal VC, and individual researchers from OpenAI and Anthropic. TechCrunch

Founded in 2025 by Jeremy Nixon, a former Google Brain researcher and creator of the AGI House hacker network community, Infinity operates under the domain infinity.inc. Nixon told TechCrunch the company grew out of his obsession with "automated invention" — the idea that AI systems can serve as a meta-technology, building and improving other technologies. TechCrunch

Nixon previously built a machine learning algorithm called Omega, which generated new ML algorithms and evaluated them automatically in a feedback loop. Infinity is now applying that same philosophy to hardware. The company is building a universal inference library designed to run on all chips, enabling automated replication of state-of-the-art research results. TechCrunch

Central to Infinity's approach is Ignition, an AI research agent that writes the low-level code required for inference on chips that compete with Nvidia's. Ignition tests, debugs, measures performance, and automatically rewrites code to improve it. Infinity claims Ignition constitutes a CUDA-level software stack — meaning it aims to match the capabilities of CUDA, Nvidia's proprietary software platform that developers currently rely on to program Nvidia GPUs. TechCrunch

AI chip maker D-Matrix, a would-be Nvidia challenger, is an Infinity customer. In a case study involving D-Matrix's Corsair platform, Ignition reduced a process that could have taken months or years down to hours or days. TechCrunch

Infinity's commercial model skips upfront licensing fees. Instead, the company takes a percentage of performance gains and cost savings, measured in tokens per second — a standard metric for how fast an AI model generates output. TechCrunch

Nixon said Infinity is in talks with other major chip and cloud companies, though he did not name them. As of July 2026, the company employs 26 people across design, operations, and engineering. The TechCrunch report is based on an interview with Nixon and does not cite an external press release or a posting on Infinity's own domain. TechCrunch

The broader context here is that Nvidia's dominance in AI data centers stems less from raw silicon capability and more from the CUDA software ecosystem that surrounds it. Developers have spent years building tools, libraries, and optimizations specifically for Nvidia GPUs, which makes switching to alternative chips expensive and slow. By tying its revenue to measured inference performance gains rather than licensing access, Infinity aligns its compensation directly with the hardware vendor's competitive positioning. If Ignition's automated code generation can genuinely match the quality of hand-tuned CUDA kernels, the cost structure of bringing a new AI accelerator to market shifts downward. TechCrunch

Worth flagging, the scope of the claims warrants scrutiny. The D-Matrix case study is a single data point, and the details originate from Infinity's own research documentation rather than an independent benchmark. Automated code generation for novel chip architectures is a substantially different challenge than optimizing for established, well-documented hardware. The claim of a CUDA-level stack is ambitious and remains unverified by third parties. TechCrunch

If Ignition functions as described, it lowers the barrier to entry for silicon alternatives. Chips from smaller vendors or new entrants could reach production-ready inference performance faster, relying on automated optimization rather than large internal compiler and kernel engineering teams. That would not displace Nvidia overnight, but it could compress the timeline for viable alternatives to reach the market. The long-term implication is that the software ecosystem advantage narrows, and hardware performance and pricing become the deciding factors for AI accelerator selection. TechCrunch

For now, Infinity is a 26-person company with a working case study and a funding round backed by investors who understand the inference landscape. Whether Ignition scales across diverse architectures is the open question, but the approach addresses a real and expensive bottleneck in AI hardware development. TechCrunch