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End-to-end computer vision platform for teams annotating data, training YOLO models, and deploying them at scale.
Developer API that gives AI agents persistent memory, retrieval, and connectors, usable both as infrastructure and a personal app.
Undetectable desktop AI assistant that feeds real-time answers during coding and technical interviews.
Google's open-source TypeScript framework for building scalable web apps, featuring signals, reactivity and first-party tooling.
Vibe-coding builder creating full-stack apps by chatting with AI.
No public pricing
No public pricing
- ✦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
- ✦Persistent, structured memory built as a knowledge graph
- ✦Sub-300ms hybrid retrieval (RAG) with reranking
- ✦Native filesystem mount for agent memory access
- ✦Connectors to Slack, Notion, Drive, Gmail, GitHub, S3
- ✦Automatic extraction from PDFs, images, and audio
- ✦User profile and behavior tracking across sessions
- ✦Real-time AI answers during technical interviews
- ✦Invisible to screen sharing and recording
- ✦Hidden from dock, tray and activity monitor
- ✦Click-through overlay
- ✦Live audio capture and transcription
- ✦Lifetime unlimited access license
- ✦Signals-based fine-grained reactivity
- ✦Built-in control flow and deferrable views
- ✦Server-side rendering and hydration
- ✦First-party routing, forms and dependency injection
- ✦AI-forward tooling and MCP resources
- ✦In-browser tutorials and playground
- ✦CodeFlying enables full-stack app creation via chat in minutes
- →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
- →Developers adding long-term memory to AI agents
- →Teams building agents that need to sync with existing tools
- →Individuals wanting one memory layer shared across multiple AI assistants
- →Getting live help on coding interview problems
- →Answering technical questions in real time
- →Avoiding detection during screen-shared interviews
- →Building scalable single-page apps
- →Enterprise web application development
- →Performance-critical front ends
- →Learning modern web development
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