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Wafer-scale AI hardware and inference cloud delivering record-fast, low-latency inference for open and frontier models.
Prompt engineering, management, and LLM observability platform.
Free tool that auto-generates conversational, browsable documentation for any public GitHub repo, from the makers of Devin.
End-to-end computer vision platform for teams annotating data, training YOLO models, and deploying them at scale.
Agentic coding platform (Cosmos) that runs software-dev agents at org scale, using a codebase context engine to cut token cost.
No public pricing
No public pricing
Free trial available
- ✦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
- ✦Prompt management
- ✦Prompt evaluations
- ✦LLM observability
- ✦Team collaboration
- ✦Version control for prompts
- ✦A/B testing of prompts
- ✦Prompt Registry
- ✦Historical backtests
- ✦Regression tests
- ✦Usage monitoring
- ✦AI-generated documentation for GitHub repos
- ✦Conversational Q&A about a codebase
- ✦Browsable index of popular repositories
- ✦Deep code indexing via Devin
- ✦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
- ✦Context Engine for codebase understanding
- ✦Agents across the full SDLC
- ✦Model routing / bring-your-own-keys
- ✦Automated code review and test coverage
- ✦CLI, MCP and native tool integrations
- ✦Enterprise security (SOC 2, ISO 42001, SSO)
- →Low-latency inference for agents and copilots
- →Real-time voice and reasoning apps
- →Fine-tuning and serving custom models
- →Scaling customer support automation with LLMs
- →Empowering non-technical teams with prompt engineering
- →Building personalized AI interactions
- →Debugging LLM agents
- →Improving content creation processes
- →Managing and monitoring prompts with a team
- →Understanding an unfamiliar codebase quickly
- →Onboarding to open-source projects
- →Answering questions about repo internals
- →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
- →Automating PR code review
- →Raising test coverage
- →Incident investigation and remediation
- →Large-scale migrations and onboarding