AI/ML Infrastructure

Groq provides the fastest AI inference platform using custom LPU hardware, delivering ultra-low latency responses for LLM applications at competitive per-token pricing.

Runpod provides GPU infrastructure and deployment workflows for AI teams training, fine-tuning, and serving models without managing raw cloud complexity.

AI training acceleration platform that dramatically speeds up deep learning training through optimized distributed computing infrastructure.

AI infrastructure company building the Mojo programming language and MAX platform for unified AI development.

Open-source vision AI platform with annotation, training, and deployment.

Hugging Face text generation inference server optimized for serving large language models in production.

Open-source ML toolkit for Kubernetes enabling portable and scalable ML workflows on cloud infrastructure.

Pipeshift helps engineering teams run real-time AI inference in production with optimized runtimes for latency and throughput SLAs, plus infrastructure orchestration for auto-scaling across...

Decentralized open-source video infrastructure network leveraging GPU owners to deliver low-cost live streaming.

Aiven provides managed open-source data infrastructure spanning databases, streaming, analytics, and search across major cloud providers.

GPU cloud infrastructure provider offering multi-GPU and multi-node clusters for large-scale AI training.

Distributed programming and infrastructure platform for ML workloads across clouds.

GPU marketplace connecting renters with providers for cost-effective AI compute with auction-based pricing.

Virtual feature store layering on top of existing infrastructure for managing ML features without migration.

Open-source ML platform for deploying, serving, and scaling production models on AWS.

Open-source MLOps framework for creating portable and production-ready ML pipelines across infrastructure.

Anyscale provides the managed platform for Ray, the open-source distributed computing framework, enabling teams to scale AI training and inference workloads across cloud infrastructure.

Platform for building and training deep learning models with PyTorch Lightning and distributed cloud compute.