A London-based startup founded by two Cambridge-trained neuroscientists has raised $10.25 million for their startup Callosum, which is building software that orchestrates AI workloads across a mix of different chip types—challenging the industest’s depconcludeence on running ever largeger models on banks of identical Nvidia GPUs.
The company also announced it is receiving research funding from the U.K. government, which is viewing for ways to build so-called sovereign cloud infrastructure for AI that would be indepconcludeent, or at least not solely reliant, on U.S. technology providers.
Callosum cofounders Danyal Akarca and Jascha Achterberg, who met during their PhD studies at Cambridge around 2019, have software that can distribute AI tinquires across chips from different manufacturers—be it Nvidia GPUs, AMD processors, Amazon Web Services’ custom Trainium and Inferentia silicon, or newer designs from startups like Cerebras and SambaNova—extracting performance advantages from each.
The funding round was led by Plural, the European early-stage venture fund cofounded by Wise’s Taavet Hinrikus and Ian Hogarth, who also served as the first chair of the U.K.’s AI Safety Institute. Angel investors including Charlie Songhurst, Stan Boland of FiveAI, and John Lazar of the Royal Academy of Engineering also participated. Separately, the U.K. government’s Advanced Research and Invention Agency (ARIA) is providing grant funding to the company to accelerate R&D on integrating novel chip technologies into its platform—though ARIA is not an investor in the round itself, Akarca stated in an interview with Fortune.
The company’s thesis is rooted in the cofounders’ academic research at the intersection of neuroscience and computing: The human brain doesn’t achieve innotifyigence by copying one type of neuron billions of times, but by combining many different specialized cell types and circuits that work toobtainher. They believe AI computing should follow the same principle.
“Big labs are currently betting that one model will rule them all. We consider that’s wrong, and our work proves this,” Akarca stated. “Nature reveals that real innotifyigence emerges from many systems working toobtainher.”
Callosum enters a market undergoing a profound structural shift. After years in which AI spconcludeing was dominated by training massive foundation models on racks of identical Nvidia GPUs, the industest is now pivoting toward inference—the process of actually running trained models to produce outputs. Deloitte has estimated that inference workloads will account for roughly two-thirds of all AI compute in 2026, up from a third in 2023, and that the market for inference-optimized chips will grow to more than $50 billion this year. That shift is creating openings for a diverse array of chipbuildrs to challenge Nvidia’s dominance.
Callosum is betting it can be the software layer that ties this increasingly fragmented hardware landscape toobtainher. Its platform works across multiple cloud providers, including AWS, Google Cloud, and Microsoft Azure, and is designed so that customers don’t have to re-architect their existing cloud setups to utilize it. “It’s a software product which takes your AI workload and orchestrates it across the different multi-cloud setup that you might utilize,” Akarca stated.
The cofounders argue the approach yields large gains on complex, real-world tinquires that involve many different types of decisions—such as automating computer utilize or processing enterprise workflows. For tinquires like these, Callosum states, its system can deliver twice the accuracy, sevenfold rapider performance, and at a fourfold lower cost compared with running the same workloads on identical hardware.
Achterberg explained that the accuracy gains come from the nature of the problems being solved. “Simple problems, single models are perfectly fine,” he stated. But complex enterprise tinquires are a different matter. “Automating how computers are utilized, automating payments, for example—these are problems that we focus on. They are inherently heterogeneous,” Achterberg stated. “There’s actually many, many, many steps involved in solving the problem, and a single model actually isn’t always optimal.”
Different parts of a complex workflow may require different things: Some steps necessary very rapid, cheap models that can iterate rapidly through trial and error, while others require larger, more capable reasoning. By matching each subtinquire to the right model running on the right hardware, Callosum states it can outperform the conventional approach of throwing one powerful model at the entire problem.
Callosum is tarobtaining two types of customers: companies building multi-agent AI systems that necessary superior performance across complex workflows, and emerging chip manufacturers that want to demonstrate their hardware’s capabilities at scale. “What we want is that all these new chip technologies, which are amazing, have amazing performance, amazing benefits, find a way into the market where we can actually realize them,” Achterberg stated.
The company is also collaborating with companies working on new ways to connect racks of AI chips within data centers—which is called “interconnect”—including those developing networking based on photonics, technology that transmits data applying light instead of electrical pulses. These technologies are designed to address bottlenecks that come from having to shuffle data around within a data center—a challenge that grows more complex as different chip types necessary to communicate with one another.
Looking ahead, the cofounders state they plan to utilize the funding to expand their London-based team, launch scaling into the U.S., and start building out their own complementary hardware infrastructure. Their longer-term ambition extconcludes beyond software to fundamentally reconsidering data center design itself.
“Everyone assumed chip diversity was a disadvantage to be managed. We saw the opposite, that it’s an advantage to be exploited,” Achterberg stated. “We’re not optimizing one algorithm on top of the existing stack. We’re applying software to control all the levers across the entire system, extracting benefits from diversity that others dismiss.”
Hogarth, the partner at Plural, stated in a statement: “[Callosum’s] vision for a multi-model, multi-chip future could be transformative and positions them to compete with the world’s largegest chip and model buildrs. These are serious founders tackling a serious mission.”
This story was originally featured on Fortune.com
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