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Free all-in-one desktop AI app to chat with your documents and run RAG and AI agents fully local and private.
End-to-end computer vision platform for teams annotating data, training YOLO models, and deploying them at scale.
Open-source React/Angular SDK and platform for embedding agentic, generative-UI copilots into apps, Slack and Teams.
TypeScript backend-as-a-service with a reactive database, server functions, auth and file storage for full-stack and AI apps.
Wafer-scale AI hardware and inference cloud delivering record-fast, low-latency inference for open and frontier models.
No public pricing
- ✦Chat with your documents (RAG)
- ✦Runs locally and offline for privacy
- ✦Supports any LLM (local or cloud)
- ✦Built-in AI agents
- ✦Handles PDFs, Word, CSV, codebases
- ✦No-code setup
- ✦Smart data annotation with SAM-powered one-click masks across six task types
- ✦Cloud training with 22+ GPU configurations from RTX 2000 Ada to B200
- ✦Support for YOLOv5 through YOLO26 model families
- ✦One-click deployment across 43 global regions with auto-scaling
- ✦Export to 18 formats including ONNX, TensorRT, and CoreML
- ✦Live training metrics and experiment comparison dashboard
- ✦React and Angular frontend SDKs
- ✦Agent-rendered generative UI
- ✦AG-UI agent-user interaction protocol
- ✦Connectors for LangChain and other frameworks
- ✦Pre-built customizable chat/sidebar components
- ✦Slack and Teams integrations
- ✦Thread and state persistence
- ✦Reactive real-time database
- ✦TypeScript server functions (queries/mutations/actions)
- ✦Built-in authentication
- ✦Cron jobs and backend workflows
- ✦File storage, text and vector search
- ✦ACID transactions; open-source/self-host
- ✦Wafer-Scale Engine AI processor
- ✦High-speed inference API (OpenAI-compatible)
- ✦Cloud, on-prem and on-device deployment
- ✦Support for GLM, Qwen, Llama, GPT-OSS and more
- ✦Fine-tuning and training on one platform
- ✦Partner access via AWS, OpenRouter, HuggingFace, Vercel
- →Privately querying your own documents
- →Running local AI without the cloud
- →Building AI agents over your data
- →Using multiple LLM providers in one app
- →Building and training custom object detection or segmentation models
- →Labeling large image/video datasets for computer vision projects
- →Deploying vision models to edge or mobile devices
- →Running quality control or defect detection in manufacturing
- →Powering retail, logistics, or agriculture vision applications
- →Adding an AI assistant to a SaaS product
- →Building agents that render interactive UI
- →Deploying copilots across Slack and Teams
- →Connecting existing agents to a frontend
- →Building real-time reactive apps
- →Backends for AI agents
- →Replacing Firebase or Supabase
- →Full-stack TypeScript development
- →Low-latency inference for agents and copilots
- →Real-time voice and reasoning apps
- →Fine-tuning and serving custom models