Bundles ASR, voice activity detection, punctuation, and speaker diarization into one pipeline, with pretrained models like Paraformer and SenseVoice. SenseVoice runs ~17x realtime on CPU; also ships streaming ASR and an OpenAI-compatible API.
Connects one LLM agent to 15+ chat platforms — QQ, WeChat Work, Feishu, Telegram, Discord, Slack — from a single self-hosted backend. Routes to OpenAI, Anthropic, Gemini, DeepSeek or Ollama, and adds a WebUI, MCP tools, and a 1000+ plugin marketplace.
Modular PyTorch-based framework for building, training, and deploying physics-informed ML models (neural operators, PINNs, GNNs, diffusion). Provides GPU‑optimized training, domain-specific datapipes for meshes/point clouds, distributed scaling and a model zoo.
Routes one API call across hundreds of LLMs from dozens of providers, with credits, fallbacks, pricing comparison, and data-policy controls for teams that need model choice without wiring every provider separately.
Aggregates alerts from dozens of monitoring tools into a single pane of glass, then deduplicates, correlates, and enriches them. Automates incident response with declarative YAML workflows — like GitHub Actions for your monitoring stack.
Open-source LLM inference and serving engine built around PagedAttention, which manages the KV cache like OS virtual memory to cut waste and raise throughput. Supports continuous batching, KV cache sharing, quantization, and an OpenAI-compatible API.
Runs AI-generated code in secure, isolated cloud sandboxes you control via Python or JavaScript SDKs; supports self-hosting (Terraform) and AWS/GCP, enabling agents and code-interpreting workflows to execute real-world tools safely.
Runs large language models entirely in C/C++ with no external dependencies, using 1.5-to-8-bit integer quantization and CPU+GPU hybrid inference to fit models larger than available VRAM. Backs Ollama, LM Studio, and most local-inference tooling.
Puts OpenAI-, Anthropic- and Ollama-compatible endpoints in front of 60+ inference backends, so existing client code runs unchanged against local models for text, vision, audio, image and embeddings. Runs CPU-only or accelerated, data stays local.
Self-hosted gateway putting OpenAI, Claude, Gemini, DeepSeek and 20+ providers behind one OpenAI-compatible endpoint. Adds per-token quotas, channel load balancing and usage billing, so teams or resellers meter keys without sharing upstream credentials.
Provides a unified platform for AI development and deployment, including the MAX serving framework and the Mojo systems programming language for writing kernels. Offers an OpenAI-compatible inference endpoint, Mojo-written CPU/GPU kernels, and tools to run hundreds of open models across diverse hardware without vendor lock-in.
Compiles one LLM into device-native binaries running on CUDA, ROCm, Metal, Vulkan, WebGPU, and CPU — same model from server to browser to phone. On Apache TVM, it ships MLCEngine with an OpenAI-compatible API across Python, JS, REST, iOS, and Android.