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Platform for building and interacting with AI-powered virtual beings.
No-code builder for custom ChatGPT-style website chatbots trained on your data for support, lead gen and engagement.
Free all-in-one desktop AI app to chat with your documents and run RAG and AI agents fully local and private.
AI coding platform and IDE that orchestrates multiple agent sessions and lets teams plug in their own AI subscriptions.
Prompt engineering, management, and LLM observability platform.
No public pricing
Free trial available
No public pricing
No public pricing
No public pricing
- ✦AI chatbot creation with unique personalities and voices
- ✦Decentralized platform for AI-native apps
- ✦Voice and video conversations with AI beings
- ✦AI agent building and sharing
- ✦Creator economy for AI apps
- ✦No-code chatbot creation
- ✦Train on files/URLs/Notion/Zendesk
- ✦Website embed widget
- ✦Conversation analytics
- ✦~95 language support
- ✦Custom branding
- ✦Chat with your documents (RAG)
- ✦Runs locally and offline for privacy
- ✦Supports any LLM (local or cloud)
- ✦Built-in AI agents
- ✦Handles PDFs, Word, CSV, codebases
- ✦No-code setup
- ✦AI coding IDE with agent orchestration
- ✦Run and manage multiple agent sessions
- ✦Task, artifact and collaboration tools
- ✦Bring-your-own AI subscription or API keys
- ✦Cloud-scale agent execution
- ✦Prompt management
- ✦Prompt evaluations
- ✦LLM observability
- ✦Team collaboration
- ✦Version control for prompts
- ✦A/B testing of prompts
- ✦Prompt Registry
- ✦Historical backtests
- ✦Regression tests
- ✦Usage monitoring
- →Interacting with AI friends like Shizuku for voice and video conversations
- →Creating AI-native apps using generative AI models
- →Building and sharing AI agents within the MyShell ecosystem
- →Website customer support
- →Lead generation
- →FAQ and audience engagement
- →Privately querying your own documents
- →Running local AI without the cloud
- →Building AI agents over your data
- →Using multiple LLM providers in one app
- →Shipping code faster with AI agents
- →Coordinating agent work across a team
- →Managing tasks and artifacts in one place
- →Running many parallel agent sessions
- →Scaling customer support automation with LLMs
- →Empowering non-technical teams with prompt engineering
- →Building personalized AI interactions
- →Debugging LLM agents
- →Improving content creation processes
- →Managing and monitoring prompts with a team