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Premium Figma and Framer UI kit with hundreds of components, variants and icons for building polished, themeable sites.
No-code platform for building and running AI agents that automate work across data, sales and support tasks.
Google Labs experiment for building and sharing AI mini-apps from natural-language prompts, no coding required.
AI coding platform routing many agents and models through one encrypted, usage-based endpoint with CLI, IDE and multi-agent execution.
Agentic terminal and cloud agent platform (Warp Terminal, Warp Agent, Oz) for developers orchestrating Claude Code, Codex, and other agents.
No public pricing
- ✦300+ Figma UI components
- ✦2,000+ Figma variants
- ✦2,116 icons
- ✦Framer-ready components and templates
- ✦Deep theming (glass, line, flat styles)
- ✦Adaptive layouts with variables
- ✦Visual canvas to orchestrate multi-agent workflows
- ✦Prebuilt specialized agents (data, support, CRM, sales)
- ✦Access to many AI models with no vendor lock-in
- ✦Slack, Teams and email agent interaction
- ✦Recurring/scheduled tasks and triggers
- ✦Enterprise security: RBAC, VPC, audit logs, spend controls
- ✦Build AI mini-apps from natural-language prompts
- ✦Visual editor for prompt/tool workflows
- ✦Share created apps with others
- ✦No-code AI app prototyping
- ✦Unified encrypted inference endpoint
- ✦Multi-agent parallel execution
- ✦CLI, IDE, and API access
- ✦App builder and remote coding agents
- ✦Chairman LLM output evaluation
- ✦35+ IDE integrations
- ✦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
- →Build a website or app UI in Figma
- →Hand off Figma designs to Framer
- →Speed up prototyping with prebuilt components
- →Automate data analysis and reporting
- →Triage support tickets and spot patterns
- →Keep a CRM updated and research prospects
- →Deploy AI agents across a team's tools
- →Prototyping an AI workflow quickly
- →Sharing a custom AI mini-app
- →Automating a task with chained prompts
- →Automating refactors, tests, and migrations
- →Running competing AI coding agents
- →Building apps from prompts
- →Integrating agents into CI/CD
- →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
