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Free all-in-one desktop AI app to chat with your documents and run RAG and AI agents fully local and private.
Developer API that gives AI agents persistent memory, retrieval, and connectors, usable both as infrastructure and a personal app.
Infrastructure company building large-scale GPU data centers and compute for AI, including Anthropic's compute buildout.
Enterprise voice-AI platform for building phone agents on dedicated infrastructure, with per-minute pricing and HIPAA/SOC2/PCI compliance.
Platform for building and interacting with AI-powered virtual beings.
No public pricing
No public pricing
Free trial available
No public pricing
- ✦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
- ✦Persistent, structured memory built as a knowledge graph
- ✦Sub-300ms hybrid retrieval (RAG) with reranking
- ✦Native filesystem mount for agent memory access
- ✦Connectors to Slack, Notion, Drive, Gmail, GitHub, S3
- ✦Automatic extraction from PDFs, images, and audio
- ✦User profile and behavior tracking across sessions
- ✦Large-scale GPU and data-center infrastructure for AI
- ✦Power acquisition and data-center design/build
- ✦Fast deployment (gigawatts in ~6 months)
- ✦Operates both hardware and software stack
- ✦AI phone agents (inbound and outbound)
- ✦No-code agent builder (Norm)
- ✦Scenario testing before launch
- ✦Omnichannel voice, SMS, iMessage and chat
- ✦Telephony and CRM integrations
- ✦Enterprise compliance and on-prem options
- ✦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
- →Privately querying your own documents
- →Running local AI without the cloud
- →Building AI agents over your data
- →Using multiple LLM providers in one app
- →Developers adding long-term memory to AI agents
- →Teams building agents that need to sync with existing tools
- →Individuals wanting one memory layer shared across multiple AI assistants
- →Training and running large AI models at scale
- →Provisioning GPU compute for AI labs
- →Building dedicated AI data-center capacity
- →Automating customer-service calls
- →IVR replacement and appointment booking
- →Outbound sales and lead qualification
- →Regulated-industry voice automation
- →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