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AI codebase assistant that chats with your repos to search, debug, review PRs, and generate docs and unit tests.
Connects Git repos to answer plain-English questions about your code with file references and dependency context.
End-to-end computer vision platform for teams annotating data, training YOLO models, and deploying them at scale.
Vibe-coding builder creating full-stack apps by chatting with AI.
Browser-based AI dev workspace by Google for full-stack apps; being sunset on 22 Mar 2027, no new workspaces.
No public pricing
Free trial available
No public pricing
- ✦Chat with your repositories
- ✦Natural-language codebase search
- ✦Fast code indexing
- ✦AI pull-request and commit review
- ✦Automated documentation generation
- ✦AI unit-test generation
- ✦Natural-language search across a codebase
- ✦Architecture explanations and dependency graphs
- ✦Bug hunter that traces issues across files
- ✦AI code review before opening a PR
- ✦Automatic documentation generation
- ✦Multi-repo support via OAuth
- ✦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
- ✦CodeFlying enables full-stack app creation via chat in minutes
- ✦Cloud workspaces for full-stack development
- ✦App Prototyping agent from natural language
- ✦Gemini AI for coding, debugging and docs
- ✦Repo import from GitHub, GitLab and Bitbucket
- ✦Web previews and Android emulators
- ✦Deploy to Firebase App Hosting, Hosting or Cloud Run
- →Onboard new developers to a codebase
- →Resolve bugs faster
- →Generate docs and tests automatically
- →Review pull requests with AI
- →Onboarding new engineers faster
- →Answering questions about a codebase
- →Understanding how components connect
- →Finding and diagnosing bugs
- →Generating documentation from code
- →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
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- →Prototyping apps from a prompt or mockup
- →Building full-stack apps in the browser
- →Collaborating and sharing preview URLs
- →Deploying and monitoring apps quickly