d-Matrix
Category: AI Infrastructure
d-Matrix develops AI inference hardware and software platforms, focusing on making generative AI commercially viable through in-memory computing technology d-Matrix was founded in 2019. The company is led by Sid Sheth. Based in Santa Clara, United States (offices in Toronto, Sydney, Bangalore, Belgrade). Team size: 250+. Total funding raised: $450M. Latest round: Series C (November 2025). Key investors include Temasek, Playground Global, M12 (Microsoft), Qatar Investment Authority, Singapore's EDBI, SK Hynix, Marvell Technology, Bullhound, Triatomic Capital.
- Founded
- 2019
- Headquarters
- Santa Clara, United States (offices in Toronto, Sydney, Bangalore, Belgrade)
- Team size
- 250+
- Total funding
- $450M
Value proposition
Ultra-low latency batched inference for generative AI, combining memory-compute integration and in-memory computing to deliver cost-effective, high-performance AI solutions with 10x faster performance and 3x better energy efficiency than GPU systems
Products and solutions
Corsair™ (world's most efficient AI computing platform for inference in datacenters), JetStream™ (custom I/O card designed for AI inference workloads), Aviator™ (inference-optimized software stack), SquadRack™ (rack-scale solution for AI inference)
Unique value
Pioneering in-memory computing architecture for AI inference, eliminating data movement between memory and compute units to drastically reduce latency and energy consumption, enabling up to 30K tokens/second at 2ms/token on Llama 70B models
Target customer
Hyperscalers, enterprises deploying AI at scale, and data center operators requiring efficient AI inference solutions
Industries served
Artificial Intelligence (Generative AI, Large Language Models), Data Center Infrastructure, Cloud Computing, Enterprise AI Solutions
Technology advantage
Proprietary digital in-memory computing (IMC) technology enables 40% higher tokens per dollar compared to competitors like NVIDIA's B200 for inference tasks, with 10x faster performance and 3x better energy efficiency
How they differentiate
d-Matrix differentiates itself by utilizing in-memory computing architecture, which eliminates the traditional von Neumann bottleneck, enabling faster and more efficient AI inference compared to competitors relying on conventional GPU/CPU architectures
Main competitors
NVIDIA, AMD, Intel, Cerebras, Groq, Graphcore
Key partnerships
HTEC (strategic partnership for AI inference solutions), GigaIO (collaboration to deliver inference solutions for enterprises), Microsoft (funding and venture capital support), Qatar Investment Authority and Singapore's EDBI (major investors in $275M Series C round), Arista Networks, Broadcom, Supermicro (SquadRack partnership)
Notable customers
Major hyperscalers via previous ventures of CEO Sid Sheth
Major milestones
2025: Achieved $2B valuation after $275M Series C fundraising, 2025: Closed oversubscribed Series C round led by global consortium, 2024: Secured $110M+ in prior funding rounds, 2019-2024: Built supply relationships with hyperscalers through previous ventures, Innovation: Pioneered in-memory computing techniques for AI inference
Growth metrics
$65.3M revenue in 2025, with 250+ employees
Market positioning
Positioned as a challenger to established players like NVIDIA in the AI inference market, with a focus on commercializing generative AI through novel in-memory computing solutions
Geographic focus
Global market focus with notable investor and regional ties in Singapore and the Middle East; operations in the United States, Canada, Australia, India, and Serbia
Patents and IP
No specific public patents listed; technological differentiator lies in proprietary IMC architecture and chiplet-based design
About Sid Sheth
20+ years in semiconductor industry, former SVP & GM at Inphi Corporation where he built a $1B+ networking business, serial entrepreneur with previous ventures supplying chips to major hyperscalers
Official website: https://www.d-matrix.ai