D-MATRIX

Sid Sheth and Sunil Gowda were both veterans of Intel and AMD. They saw the same problem from the inside: the transformer architecture used in LLMs has a memory bandwidth problem.

When you run inference on a GPT-style model, you are constantly reading enormous weight matrices from memory, and the memory bandwidth bottleneck limits speed and drives up energy costs. NVIDIA's GPU architecture is great for training (parallel math) but less optimal for inference (random memory access patterns).

D-Matrix's Corsair chip uses a fundamentally different architecture — compute-in-memory — that embeds compute units directly in the memory arrays, eliminating the bottleneck.

D-Matrix sells AI inference accelerator chips and systems designed specifically for large language model inference — running AI models at deployment, not training. Its chips use a compute-in-memory (CIM) architecture, which reduces the energy cost of moving data between memory and processing units, one of the fundamental bottlenecks in transformer model inference.

Revenue model is chip and system sales to data centers and cloud providers.

Corsair compute-in-memory AI inference accelerator, d-Matrix software stack (model compatibility layer), reference server designs

D-Matrix targeted hyperscalers and large enterprises deploying LLMs at scale, where inference cost is a real operating line item. Microsoft's strategic investment signals potential cloud deployment.

It positioned Corsair as the TCO (total cost of ownership) winner for inference workloads — not claiming to beat NVIDIA on raw performance, but on cost per inference query at scale.

NVIDIA has 90%+ market share in AI accelerators and enormous software ecosystem advantages (CUDA). Any alternative chip architecture requires software compatibility work to integrate with existing AI frameworks (PyTorch, TensorFlow).

Early AI chip companies (Graphcore, Cerebras) found this integration cost higher than expected. D-Matrix's inference-specific positioning is a deliberate attempt to find a wedge market where NVIDIA is not the obvious default.

Microsoft (strategic), Playground Global, Standard Investments, SK Telecom, Nautilus Venture Partners