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Raycast
✓ verifiedFreemium
A fast, keyboard-driven Mac/Windows launcher with an extension store and built-in AI commands for power users who live in shortcuts.
1.1M visits/mo3.4K saves
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Numa
✓ verifiedPaid
AI operating system for car dealerships with voice AI, a smart inbox and agents that capture leads and lift service revenue.
207K visits/mo337 saves
Pricing
Pro (with AI): $8/month
Free trial available
No public pricing
No public pricing
No public pricing
Core features
- ✦Extendable command-bar launcher for macOS and beta Windows support
- ✦Thousands of third-party extensions from a public store
- ✦Built-in AI chat and custom AI command automation
- ✦Clipboard history, window management, and calculator utilities
- ✦Text snippets and quicklinks for repetitive actions
- ✦Hotkeys and aliases for common apps and commands
- ✦Team plan for sharing snippets, quicklinks, and extensions
- ✦Lifelike voice AI agents
- ✦24/7 availability
- ✦Customer-led conversational platform
- ✦Integration with enterprise systems
- ✦Voice AI with full customer context
- ✦AI-native Smart Inbox across channels
- ✦LiveCSI real-time satisfaction monitoring
- ✦Service Advisor Agent
- ✦Heat Case and Opportunity Agents
- ✦Mobile app
- ✦Coding education platform for beginners
- ✦Curriculum on Next.js, Vercel, and AI
- ✦AI-powered app development
- ✦Live events and hackathons
- ✦Coding community
- ✦AI-centric platform for software engineers
- ✦Nia AI for code understanding
- ✦Context management and codebase understanding tools
Use cases
- →Launching apps and running quick commands without leaving the keyboard
- →Automating repetitive text and file tasks with snippets and quicklinks
- →Getting AI answers or writing help without switching apps
- →Sharing productivity tooling and extensions across a team
- →Answering customer service calls
- →Providing information and support
- →Resolving customer issues
- →Automating call center operations
- →Answering dealership calls and messages
- →Rescuing and booking service leads
- →Resolving customer complaints (heat cases)
- →Boosting service-advisor productivity
- →Learning to code and build AI-powered applications
- →Developing AI agents that can work with code safely and effectively
- →Empowering developers to orchestrate AI agents across the software lifecycle
- →Improving context management and codebase understanding for AI agents
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