4/747 → 8/650; +0.70 percentage points of formation share.
The Fastest Multimodal Inference OS. Cumulus Labs lets engineering teams ship AI in production without needing a dedicated ML platform team. Right now, companies building AI products are forced to stitch together separate vendors for routing, observability, evaluation, fine-tuning, and inference. This fragmented approach is brittle, expensive, and is a common reason enterprises fail with AI. We replace that entire stack with a single unified platform. Developers can keep their existing code while instantly upgrading to a unified platform that handles routing, semantic caching, continuous shadow evaluation, simulated data, and one-click fine-tuning. Behind the platform is Ion, our proprietary inference engine running on a custom NVIDIA Grace GPU fleet. Ion uses in-house custom GPU kernels to deliver 30 to 50 percent more throughput than standard vLLM or SGLang, giving our customers SOTA i
The Networking Layer of AI. Up to 80% of the most advance AI compute chips sits idle because of slow networking. Piris Labs builds photonic based networking solutions to enable fast, scalable, and low cost AI workload execution infrastructure.
Accelerated Physics Kernels for Computational Engineering. Axial develops accelerated software for geometric computation, physical simulation, and manufacturing. Our GPU-native kernels provide programmable building blocks for the computational engineering cycle. They make existing workflows faster and less expensive while enabling engineering teams to explore substantially larger design spaces.
AI that makes AI fast. Wafer builds AI agents that work as autonomous performance engineers, optimizing GPU kernels for AI inference. Our product is serverless and dedicated inference for the world’s fastest open source LLMs, achieved by Wafer's autonomous performance engineers.
Making AI run fast on any hardware.. Luminal builds an ML framework and compiler that generates GPU code. Our stack 10x's model speed while simplifying deployment and cutting idle GPU costs Github: https://github.com/luminal-ai/luminal Discord: https://discord.gg/APjuwHAbGy
We sell GPUs.. Lilac sells flexible GPU contracts and runs the software layer on top: monitoring, bare-metal provisioning, and managed Kubernetes and Slurm. We also run this layer for GPU cloud providers as their named operations and support partner.
Design a chip in minutes. Partcl modernizes chip design automation with physics-informed models powered by GPU acceleration. Our tools run up to 700× faster than legacy solutions, cutting weeks off development and unlocking AI-driven optimization.
quantum-accelerated AI servers. We’re building quantum-accelerated AI servers so organizations building AI can exponentially speed up training and inference. And we’re making tools for AI researchers to integrate quantum capabilities into AI models and workflows.
A primary internal company segment within GPU Compute Infrastructure, derived deterministically from the shared yc industry “Infrastructure”. This is a classification of current window members, not a causal layer or a separate time trend.
A primary internal company segment within GPU Compute Infrastructure, derived deterministically from the shared yc industry “Engineering, Product and Design”. This is a classification of current window members, not a causal layer or a separate time trend.
Measured-window members of GPU Compute Infrastructure that could not be assigned to a narrower shared YC tag or industry without forcing a classification.
No comparable outside activity is connected yet.
These share a word with “GPU Compute Infrastructure” but are tracked as separate categories. The real overlap below is the actual share of GPU Compute Infrastructure’s companies also found in that category — not a guess.
Cambrian Signal, “GPU Compute Infrastructure,” publication yc-2026-10-22-semantic-v8, snapshot October 22, 2026.
cambrian.jafar.com/formation/gpu-compute-infrastructure