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Devzery
✓ verified
AI API regression-testing solution for streamlined QA and faster releases.
41K visits/mo2.0K saves
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Code to Flow
✓ verifiedFreemium
AI tool that converts code into interactive flowcharts, sequence and class diagrams with plain-English explanations.
12K visits/mo
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Rerun
✓ verifiedFreemium
Open-source SDK and viewer for logging, querying, and visualizing multimodal robotics data, with a paid managed Hub for scale.
88K visits/mo
Pricing
No public pricing
Free: $0 (3 flowcharts/day)
Monthly: $9.99/mo (unlimited)
Lifetime: $66.99 one-time (unlimited)
Open Source SDK: Free (Apache-2.0/MIT)
Core features
- ✦AI-Powered Test Case Generation
- ✦Automated API Regression Testing
- ✦Collaborative Bug Tracking
- ✦Integrations with Project Management and CI/CD Tools
- ✦Effortless API Documentation
- ✦Unified Platform for Different Testing Phases
- ✦Code-to-flowchart, sequence, class and user-journey diagrams
- ✦AI code explanations
- ✦Support for major languages
- ✦Export to PNG, SVG, PDF
- ✦Editable, customizable diagrams
- ✦Shareable links; code not stored
- ✦Open-source Python, Rust, and C++ logging SDK
- ✦Interactive desktop and web viewer for reviewing recordings
- ✦SQL and dataframe queries across logged data
- ✦Column-chunk .rrd storage format for multimodal data
- ✦PyTorch dataloader for training directly on recordings
- ✦Commercial Hub with managed catalog, SSO, and byte-range indexing
- ✦Used in robotics projects like LeRobot, Brush, and PyCuVSLAM
Use cases
- →AI-Powered Test Case Generation: Devzery’s AI engine analyzes your PRD or project details to generate API test cases.
- →Test Suite & HTTP Coverage Metrics: Track test coverage and HTTP distribution metrics to ensure all critical aspects of your APIs are covered.
- →Precise Bug Tracking with AI: Automatically generate detailed bug reports with status, related test cases, expected vs. actual results, and error descriptions.
- →Understand and debug complex logic
- →Learn programming concepts visually
- →Create diagrams for documentation
- →Explain code in reviews
- →Robotics teams debugging calibration and training runs
- →Visualizing and querying large multimodal sensor datasets
- →Streaming training data mixes directly to GPUs at scale
- →Sharing annotated recordings across a robotics engineering team
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