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AI coding platform and IDE that orchestrates multiple agent sessions and lets teams plug in their own AI subscriptions.
Wafer-scale AI hardware and inference cloud delivering record-fast, low-latency inference for open and frontier models.
AI cloud offering model APIs, GPU instances, and serverless GPUs; high traffic.
End-to-end computer vision platform for teams annotating data, training YOLO models, and deploying them at scale.
Free all-in-one desktop AI app to chat with your documents and run RAG and AI agents fully local and private.
No public pricing
No public pricing
No public pricing
- ✦AI coding IDE with agent orchestration
- ✦Run and manage multiple agent sessions
- ✦Task, artifact and collaboration tools
- ✦Bring-your-own AI subscription or API keys
- ✦Cloud-scale agent execution
- ✦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
- ✦Model APIs
- ✦GPU Instances
- ✦Serverless GPUs
- ✦Custom Model Deployment
- ✦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
- ✦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
- →Shipping code faster with AI agents
- →Coordinating agent work across a team
- →Managing tasks and artifacts in one place
- →Running many parallel agent sessions
- →Low-latency inference for agents and copilots
- →Real-time voice and reasoning apps
- →Fine-tuning and serving custom models
- →Deploy AI models for various applications using a simple API.
- →Scale AI applications with serverless GPUs.
- →Access high-performance GPUs for demanding workloads.
- →Deploy custom models with guaranteed performance and scalability.
- →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
- →Privately querying your own documents
- →Running local AI without the cloud
- →Building AI agents over your data
- →Using multiple LLM providers in one app