Tools

A fully managed service that enables data scientists and developers to build, train, and deploy machine learning models quickly and easily. Includes hosted Jupyter notebooks, distributed training, and model monitoring.

All-in-one desktop and Docker app for chatting with documents using RAG. Supports local and cloud LLMs with multi-user workspaces and agent tools.

Open-source AI coding assistant for VS Code and JetBrains. Supports any LLM (local or cloud) for autocomplete, chat, and inline editing.

A unified platform for building, training, and deploying machine learning models and AI applications at scale. Includes pre-trained APIs, AutoML for no-code model building, and custom training services.

Open-source ChatGPT alternative that runs 100% offline. Supports multiple local and remote AI engines with an extensible plugin system.

Run LLMs as a single executable file. Combines a model and runtime into one file that runs on any OS without installation — created by Mozilla.

Desktop app for discovering, downloading, and running local LLMs on your computer. Supports GGUF models with a built-in chat UI and local server.

Microsoft's comprehensive suite of AI services and tools for building intelligent apps. Includes pre-built APIs for vision, speech, language, and decision-making, plus custom model training capabilities.

Open-source platform for managing the ML lifecycle including experiment tracking, model registry, and deployment. Works with any ML framework.

Comprehensive guide to the Model Context Protocol (MCP), a standard for communication between AI models and applications. Learn about the protocol specification, implementation details, and best practices.

Run large language models locally with a simple CLI and REST API. Supports Llama, Mistral, Gemma, Phi, and many other models out of the box.

Self-hosted, feature-rich web UI for LLMs. Compatible with Ollama and OpenAI-compatible APIs. Supports RAG, multimodal models, and multi-user management.

Open-source app framework for Machine Learning and Data Science teams. Turn data scripts into shareable web apps in minutes with pure Python.

The most popular self-hosted web UI for running local LLMs. Supports dozens of model formats with extensions for RAG, TTS, and character personas.

Industry-standard MLOps platform for experiment tracking, dataset versioning, model evaluation, and hyperparameter optimization. Used by most AI labs.