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Connects Git repos to answer plain-English questions about your code with file references and dependency context.
Undetectable desktop AI assistant that feeds real-time answers during coding and technical interviews.
AI screenplay-coverage tool returning structured coverage reports and development notes per script in minutes.
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.
No public pricing
No public pricing
- ✦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
- ✦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
- ✦11-section AI coverage reports
- ✦Scene-by-scene development notes
- ✦AI chat assistant for deeper insights
- ✦Script dashboard and organization
- ✦Results in minutes
- ✦Free screenwriting tools (formatter, character builder)
- ✦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
- →Onboarding new engineers faster
- →Answering questions about a codebase
- →Understanding how components connect
- →Finding and diagnosing bugs
- →Generating documentation from code
- →Getting live help on coding interview problems
- →Answering technical questions in real time
- →Avoiding detection during screen-shared interviews
- →Getting screenplay coverage quickly
- →Development notes before rewrites
- →Evaluating scripts for production
- →Iterating affordably on drafts
- →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