Stainless

Generate SDKs and API documentation from OpenAPI specs

Fern is a platform that generates idiomatic client SDKs and beautiful API documentation from OpenAPI specifications. It produces type-safe SDKs for TypeScript, Python, Java, Go, Ruby, and C# with features like pagination, retries, and streaming built in. The documentation includes API reference, guides, and an AI-powered search assistant. Used by companies like Cohere, ElevenLabs, and Merge.

Auto-generate SDKs and docs from backend routes

Speakeasy uses AI to parse backend API routes and auto-generate production-ready SDKs in multiple languages alongside OpenAPI documentation. It ensures that client libraries and documentation always match the current backend implementation, eliminating the drift between API code, SDK behavior, and documentation that plagues most API-first teams as their services evolve.

Heterogeneous CPU-GPU inference and SFT for large MoE models

Open-source framework for running and fine-tuning large Mixture-of-Experts models with heterogeneous CPU-GPU execution, optimized kernels, limited VRAM and SGLang or LLaMA-Factory integrations.

Official Kubernetes and Helm reference stack built on the vLLM inference engine

Official vLLM reference implementation for scaling the existing inference engine on Kubernetes with Helm, request routing, KV-cache offload, autoscaling and Prometheus/Grafana observability.

Distributed inference orchestration above vLLM, SGLang and TensorRT-LLM

Open-source, datacenter-scale orchestration layer that coordinates vLLM, SGLang and TensorRT-LLM across nodes with disaggregated serving, KV-aware routing, multi-tier cache management and automatic scaling.

Open-source GPU control plane for scalable AI model serving

Open-source GPU cluster manager that configures vLLM, SGLang, TensorRT-LLM or custom engines, serves models through compatible APIs, and provisions SSH-accessible GPU instances across on-premises, Kubernetes and cloud environments.

Disaggregated KV cache storage and transfer for LLM serving

Open-source infrastructure for disaggregated LLM serving that pools KV caches across prefill and decode workers, with high-performance transfer, distributed storage and integrations for vLLM and SGLang.

Reusable KV cache infrastructure for scalable LLM inference

Open-source KV cache management layer that persists, offloads and reuses model key-value caches across requests and serving engines to reduce repeated prefill work and improve inference throughput.