Strapi

Open data platform wrapping any SQL database with instant APIs

Directus is a database-first open data platform that wraps any existing SQL database with instant REST and GraphQL APIs, a no-code admin dashboard, and built-in authentication. Unlike traditional headless CMS platforms that impose their own data model, Directus introspects your existing schema and works on top of it — supporting PostgreSQL, MySQL, SQLite, MS SQL, MariaDB, and CockroachDB out of the box.

AI-ready PDF parser with benchmark-leading accuracy

OpenDataLoader PDF is a high-performance parser that extracts structured, AI-ready data from PDFs with industry-leading 0.907 benchmark accuracy. Combines deterministic local processing with optional AI hybrid mode for complex layouts, OCR support across 80+ languages, formula extraction in LaTeX, chart descriptions, and built-in prompt injection filtering. Available as Python, Node.js, and Java SDKs for seamless RAG pipeline and data preparation integration.

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.