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Macroscope
✓ verifiedFreemium
AI tool for engineering teams that automates code review, status updates, and answers questions about what's changing in code.
21K visits/mo
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Code Autopilot
✓ verifiedFreemium
AI GitHub companion that summarizes PRs, answers questions and proposes fixes inside issues and pull requests.
Pricing
No public pricing
No public pricing
No public pricing
No public pricing
Discover (Livechat): Free
Karate Kid (Livechat): $29 per month
Samurai (Livechat): $79 per month
Shogun (Livechat): $199 per month
Enterprise (Livechat): Custom
Discover (AI Chatbot): Free
Karate Kid (AI Chatbot): $29 per month
Samurai (AI Chatbot): $79 per month
Shogun (AI Chatbot): $199 per month
Enterprise (AI Chatbot): Custom
Explorer plan (AI Community Manager): Free
Essential plan (AI Community Manager): $8 per month
ChatGPT Pro Plan (AI Community Manager): $29 per month
Enterprise flex plan (AI Community Manager): Custom
Discover (Webhooks): Free
Lucky offer (Webhooks): $149 per month
Enterprise (Webhooks): Custom
Discover (AI Assistant for linkedin): Free
Monthly deal (AI Assistant for linkedin): 9€ per month
Monthly deal (AI Assistant for linkedin): 59€ per month
Enterprise (AI Assistant for linkedin): Custom
Core features
- ✦AI code review
- ✦Automatic engineering status updates
- ✦Agent that answers questions and takes action
- ✦Metrics on coding time and project focus
- ✦Pushed vs landed tracking
- ✦Commit and contributor insights
- ✦Fast tensor operations
- ✦Differentiable tensors for gradient-based optimization
- ✦Network connectivity
- ✦Integration with Bun and Flashlight
- ✦Support for GPU computation with CUDA (Linux) and CPU computation (macOS)
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- ✦Chat inside GitHub issues and PRs
- ✦Task-to-implementation plans with code
- ✦Automatic bug-fix suggestions
- ✦Pull-request summaries for faster review
- ✦Full-codebase context
- ✦GitHub-native integration
- ✦AI Chatbot
- ✦Livechat
- ✦Callbot
- ✦Webhooks
- ✦AI Community Manager
- ✦AI Assistant for Linkedin
Use cases
- →Automating code reviews
- →Keeping stakeholders updated on engineering progress
- →Understanding what's changing in a codebase
- →Tracking team productivity metrics
- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
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- →Speeding up pull-request reviews
- →Implementing features from task descriptions
- →Debugging with AI-proposed solutions
- →Answering questions about a repo
- →Boosting a solo developer's output
- →Automating customer support
- →Managing online communities
- →Generating leads
- →Automating business workflows
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