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Infrastructure company building large-scale GPU data centers and compute for AI, including Anthropic's compute buildout.
Managed AI ranking engine powering personalized search, recommendations, and feeds via a SQL-like query language.
End-to-end computer vision platform for teams annotating data, training YOLO models, and deploying them at scale.
Open-source node-based engine for visual AI, giving pros granular control to build image, video, and 3D generation workflows.
Wafer-scale AI hardware and inference cloud delivering record-fast, low-latency inference for open and frontier models.
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Free trial available
- ✦Large-scale GPU and data-center infrastructure for AI
- ✦Power acquisition and data-center design/build
- ✦Fast deployment (gigawatts in ~6 months)
- ✦Operates both hardware and software stack
- ✦ShapedQL SQL-style query interface for retrieval and ranking
- ✦Hybrid semantic and keyword search
- ✦Continuous learning from user feedback signals
- ✦30+ native data connectors for warehouses and streams
- ✦Sub-50ms query latency
- ✦Python and TypeScript SDKs plus MCP support
- ✦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
- ✦Node-based workflow canvas
- ✦Simplified App Mode view
- ✦Community workflow templates and hub
- ✦Comfy Desktop (local) and Comfy Cloud
- ✦Comfy API for production endpoints
- ✦60,000+ nodes and many models
- ✦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
- →Training and running large AI models at scale
- →Provisioning GPU compute for AI labs
- →Building dedicated AI data-center capacity
- →Personalizing 'for you' content feeds
- →Building product recommendation systems
- →Powering RAG retrieval with behavioral ranking
- →Adding hybrid search to an e-commerce site
- →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
- →Building custom image/video/3D pipelines
- →VFX, advertising, gaming, and ecommerce content
- →Running workflows on cloud GPUs
- →Deploying workflows as production APIs
- →Low-latency inference for agents and copilots
- →Real-time voice and reasoning apps
- →Fine-tuning and serving custom models