Organizations by Tag: AI-Infrastructure — Companies, Research Labs, and Open Source Projects Building Scalable Model Platforms
Explore organizations tagged with ai-infrastructure to discover companies, research labs, and open source projects that design, deploy, and operate scalable model platforms. This tags pillar results list highlights real-world adoption across distributed training, model serving, GPU cluster orchestration, real-time inference, end-to-end MLOps pipelines, feature stores, observability, and cost-optimized deployment patterns. Use the filtering UI to narrow results by deployment stack (Kubernetes, Docker, Triton Inference Server, ONNX Runtime), architecture (data parallelism, model parallelism, sharded training), and production metrics (inference latency, throughput, SLOs). View technical profiles, code links, benchmarks, and integration notes to compare providers, identify contributors, and evaluate collaboration or hiring opportunities; start exploring to map adoption patterns and implementation details for your AI infrastructure roadmap.
