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AI codebase assistant that chats with your repos to search, debug, review PRs, and generate docs and unit tests.
AI tool for engineering teams that automates code review, status updates, and answers questions about what's changing in code.
Google's AI coding assistant for code completion, generation, chat and review across IDEs and GitHub.
AI-powered SQL optimizer for PostgreSQL and MySQL that auto-rewrites and indexes queries; now free as part of Aiven.
No public pricing
No public pricing
Free trial available
No public pricing
No public pricing
No public pricing
- ✦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
- ✦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
- ✦AI code completion and suggestions
- ✦Natural-language code generation
- ✦In-IDE chat assistance
- ✦AI code review
- ✦IDE integrations (VS Code, JetBrains, etc.)
- ✦GitHub integration
- ✦Automatic SQL query optimization
- ✦Query rewriting and indexing suggestions
- ✦Non-intrusive performance sensor
- ✦Ongoing performance insights
- ✦Database cost-reduction recommendations
- ✦PostgreSQL and MySQL support
- →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
- →Automating code reviews
- →Keeping stakeholders updated on engineering progress
- →Understanding what's changing in a codebase
- →Tracking team productivity metrics
- →Speeding up coding with AI completions
- →Generating code from plain-language prompts
- →Getting in-editor help and explanations
- →Reviewing pull requests with AI
- →Understanding unfamiliar codebases
- →Optimizing slow SQL queries
- →Monitoring database performance
- →Reducing database CPU and storage costs
- →Getting indexing recommendations