d-Matrix, a pioneer in generative AI inference compute for data centers, has raised $275 million in a Series C funding round, valuing the company at $2 billion and bringing its total funding to $450 million. The new capital will accelerate d-Matrix’s global expansion, advance its product roadmap, and support large-scale deployments of its high-performance, energy-efficient data center inference platform for hyperscale, enterprise, and sovereign clients.
The oversubscribed round drew top-tier investors from Europe, North America, Asia, and the Middle East. Co-led by BullhoundCapital, Triatomic Capital, and Temasek, the round also welcomed new participants including the Qatar Investment Authority (QIA) and EDBI, alongside follow-on investments from M12, Microsoft’s Venture Fund, Nautilus Venture Partners, Industry Ventures, and Mirae Asset.
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d-Matrix’s full-stack inference platform integrates breakthrough compute-memory architecture, high-speed networking, and inference-optimized software to deliver up to 10× faster performance, 3× lower costs, and 3–5× better energy efficiency compared to traditional GPU-based systems. Its Corsair inference accelerators, JetStream NICs, and Aviator software enable up to 30,000 tokens per second at 2ms per token on a Llama 70B model. The compute-dense design allows a single rack to run models with up to 100 billion parameters at remarkable speed.
This leap in efficiency directly addresses AI sustainability challenges. By enabling one data center to handle workloads previously requiring ten, d-Matrix helps enterprises reduce energy consumption while offering cost-effective, high-performance AI services.
“From day one, d-Matrix has been uniquely focused on inference. When we started d-Matrix six years ago, training was seen as AI’s biggest challenge, but we knew that a new set of challenges would be coming soon,” said Sid Sheth, CEO and co-founder of d-Matrix. “We predicted that when trained models needed to run continuously at scale, the infrastructure wouldn’t be ready. We’ve spent the last six years building the solution: a fundamentally new architecture that enables AI to operate everywhere, all the time. This funding validates that vision as the industry enters the Age of AI Inference.”
Investor confidence highlights d-Matrix’s differentiated technology, rapid customer growth, and expanding network of global partners, including the recently announced SquadRack reference architecture with Arista, Broadcom, and Supermicro. The company’s roadmap features 3D memory-stacking innovations and a customer-focused go-to-market strategy, establishing d-Matrix as a cornerstone of AI infrastructure.
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“As the AI industry’s focus shifts from training to large-scale inference, the winners will be those who anticipated this transition early and built for it,” said Per Roman, Founder of BullhoundCapital. “d-Matrix stands out not only for its technical depth but for its clear strategic vision. The team understood before anyone else that inference would define the economics of AI and they’re executing brilliantly on that insight.”
“AI inference is becoming the dominant cost in production AI systems, and d-Matrix has cracked the code on delivering both performance and sustainable economics at scale,” said Jeff Huber, General Partner at Triatomic Capital. “With Sid, Sudeep, and their world-class team, plus an exceptional ecosystem of partners, d-Matrix is redefining what’s economically possible in AI infrastructure.”
“The explosion in AI inference demand shows us that efficiency and scalability can be key contributors to revenue capture and profitability for hyperscalers and AI factories,” said Michael Stewart, Managing Partner at M12, Microsoft’s Venture Fund. “d-Matrix is the first AI chip startup to address contemporary unit economics in LLM inference for models of a range of sizes that are growing the fastest, with differentiated elements in the in-memory product architecture that will sustain the TCO benefits with leading latency and throughput.”
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