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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.

AMW Analysis

d-Matrix develops AI inference hardware and software built around in-memory computing, aiming to make generative AI commercially viable through memory-compute integration. Founded in 2019 and based in Santa Clara with offices in Toronto, Sydney, Bangalore, and Belgrade, the company positions its architecture as delivering faster, more energy-efficient batched inference than conventional GPU-based systems. It has raised $450 million to date, backed by investors including Temasek, Playground Global, M12, Qatar Investment Authority, Singapore's EDBI, SK Hynix, Marvell Technology, Bullhound, and Triatomic Capital.

Recent news flow shows the company expanding on multiple fronts. Its November 2025 Series C added $275 million, valuing the company at $2 billion, built around its Corsair chip and in-memory compute architecture. In April 2026, d-Matrix acquired GigaIO's SuperNODE rack-scale platform and FabreX PCIe Gen 5 AI fabric, extending its offering into full data-center infrastructure and adding engineering talent, with reported efficiency gains for large models. Most recently, a partnership with Nvidia was announced, a notable development given the two companies' positions in the inference silicon space.

AMW analysis, generated from 3 tracked news signals.

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), SuperNODE (rack-scale AI infrastructure technology, acquired from GigaIO, April 2026), FabreX™ (PCIe-based memory fabric, acquired from GigaIO, April 2026)

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 (data center business acquired by d-Matrix, April 2026 — SuperNODE and FabreX technology), 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), Infineon Technologies (power delivery collaboration for Corsair, May 2026), TSMC and Alchip Technologies (Corsair manufacturing partnership, N6 process)

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, 2026-04: Acquired GigaIO's data center business (SuperNODE, FabreX memory fabric) to expand rack-scale AI capabilities, 2026-05: Partnered with Infineon Technologies on power delivery for Corsair accelerator, 2026-06: Corsair AI inference platform entered full production; began shipments to hyperscalers, neoclouds, and frontier AI labs, 2026-06: Corsair won AI Breakthrough Award for AI Processor Innovation

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

Latest news about d-Matrix

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d-Matrix - AI Startup Profile | AI Market Watch