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Open-source, AI-powered command-line utilities installed via npm for databases, scripts, and AI interactions in the terminal.
AI API regression-testing solution for streamlined QA and faster releases.
One-click bug-reporting tool that auto-captures console, network logs and repro steps for developers.
Vibe-coding builder creating full-stack apps by chatting with AI.
Agentic terminal and cloud agent platform (Warp Terminal, Warp Agent, Oz) for developers orchestrating Claude Code, Codex, and other agents.
No public pricing
No public pricing
Free trial available
- ✦AI-powered CLI utilities
- ✦npm install (command-ai)
- ✦Terminal-based AI interactions
- ✦Database and script helpers
- ✦Open-source (GitHub)
- ✦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
- ✦One-click bug capture via browser extension
- ✦Automatic repro steps
- ✦Console, network and device logs
- ✦Instant replay of recent activity
- ✦Backend tracing and an AI debugger
- ✦Integrations with Jira, Linear, GitHub and Slack
- ✦CodeFlying enables full-stack app creation via chat in minutes
- ✦Modern terminal rebuilt for agentic coding workflows
- ✦Warp Agent with multi-agent orchestration and model routing
- ✦Oz platform for launching agents into the cloud via SDK, CLI, or terminal
- ✦Codebase indexing and granular permission controls
- ✦Team-wide usage visibility and spend/credit caps
- ✦Open-source terminal core
- →Running AI tasks from the terminal
- →Scripting and automation with AI
- →Database interactions via CLI
- →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.
- →Filing detailed bug reports
- →Reproducing issues faster in QA
- →Sharing debug context with engineers
- →Triaging support bug reports
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- →Developers who want an AI-assisted terminal for daily coding
- →Teams orchestrating multiple coding agents (Claude Code, Codex) together
- →Engineering orgs needing governance over agent-driven development
- →Companies moving agent workflows from local machines to the cloud