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GitLoop
✓ verifiedFree trial
AI codebase assistant that chats with your repos to search, debug, review PRs, and generate docs and unit tests.
👁 11K/mo♥ 2.7K
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✓ verifiedFreemium
Open-source AI coding assistant offering autocomplete and chat in IDEs; the company was acquired by Cursor.
👁 775K/mo
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QA.tech
✓ verifiedPaid
AI agent-based end-to-end testing platform for SaaS teams that runs exploratory and PR-triggered tests without maintaining test scripts.
👁 29K/mo♥ 8.7K
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Eraser AI
✓ verifiedFreemium
AI co-pilot for technical diagrams and design docs, with diagram-as-code and integrations for engineering teams.
👁 873K/mo♥ 41K
Pricing
No public pricing
No public pricing
Free trial available
No public pricing
No public pricing
Free: $0 (3 files, 3 AI diagrams)
Starter: $15/user/mo billed annually (40 AI diagrams)
Business: $45/user/mo billed annually (250 AI diagrams, SSO)
Core features
- ✦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)
- ✦Chat with your repositories
- ✦Natural-language codebase search
- ✦Fast code indexing
- ✦AI pull-request and commit review
- ✦Automated documentation generation
- ✦AI unit-test generation
- ✦Open-source AI code assistant
- ✦Customizable autocomplete
- ✦In-editor AI chat
- ✦Community-built coding agent
- ✦AI agents that visually explore and test UI like a real user
- ✦Automatic PR-triggered test runs via GitHub/Vercel preview integration
- ✦Self-healing tests that adapt to UI and workflow changes
- ✦Mobile web, iOS, and Android app testing support
- ✦Detailed debugging with screenshots, logs, and failure reasoning
- ✦Cloud-native execution with no source-code access required
- ✦AI-generated diagrams from prompts
- ✦Diagram-as-code editing
- ✦Markdown design docs
- ✦Eraserbot auto-updating codebase diagrams
- ✦Integrations: GitHub, Notion, Confluence, VS Code
- ✦Export to PNG/SVG/PDF/MD and MCP server
Use cases
- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
- →Onboard new developers to a codebase
- →Resolve bugs faster
- →Generate docs and tests automatically
- →Review pull requests with AI
- →Get AI code completions while coding
- →Ask questions about code in the editor
- →Build on an open-source coding-agent foundation
- →Engineering teams wanting regression testing without maintaining scripts
- →SaaS companies needing continuous QA feedback on every pull request
- →Teams replacing manual QA hours with automated agent-driven testing
- →Create architecture and cloud diagrams fast
- →Write and maintain design docs
- →Keep codebase diagrams up to date
- →Embed live diagrams in Notion/Confluence
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