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Agentic AI platform with a coding desktop app, CLI, and cloud agents for autonomous software development and office work.
Native macOS app that unifies 300+ AI models in one private workspace with agents, MCP tools, and one-time licensing.
Open-source desktop app for running AI chat models locally or via APIs, as a private ChatGPT alternative.
Enterprise AI agent control plane that orchestrates coding agents across the SDLC on any model, deployable on-prem or air-gapped.
No public pricing
Free trial available
Free trial available
No public pricing
No public pricing
Free trial available
- ✦Multi-agent collaboration for end-to-end tasks
- ✦Persistent memory and custom rules
- ✦Extensible skills and plugins
- ✦Rich context across code, images, and directories
- ✦Automatic codebase documentation generation
- ✦Terminal-native CLI and JetBrains IDE plugin
- ✦Cloud-hosted agents for enterprise use
- ✦Switch across 300+ hosted and local AI models
- ✦Native macOS app with global shortcut and screenshot-to-answer
- ✦Reusable agents, projects, and forked chats
- ✦Multimodal analysis of PDFs, images, and code
- ✦MCP tools and code execution
- ✦Local chat storage with encryptable API keys
- ✦Run open-source LLMs locally
- ✦Connect to online models (OpenAI, Claude, Gemini)
- ✦Private, offline-capable AI chat
- ✦Open source and self-hostable
- ✦Model library via Hugging Face
- ✦Cross-platform desktop app
- ✦Orchestration of AI agents across the SDLC
- ✦Model-agnostic, bring-your-own-model support
- ✦On-prem, VPC, and air-gapped deployment
- ✦Hybrid Context Engine for codebase-scoped answers
- ✦Spec, Agent, and Chat modes
- ✦Reusable skills, tool permissions, and coding-standard rules
- →Autonomous feature development in large codebases
- →Terminal-based AI pair programming
- →Cross-department task automation for legal, finance, HR
- →Onboarding developers to unfamiliar codebases
- →Using multiple AI providers in one place
- →Explaining or fixing on-screen content instantly
- →Building reusable task-specific agents
- →Analyzing documents and screenshots privately
- →Private local AI chat
- →Using multiple models in one app
- →Avoiding cloud data sharing
- →Experimenting with open models
- →Migrating and modernizing legacy .NET code
- →Running autonomous feature and refactor workflows
- →Enforcing company coding standards across teams
- →Answering questions and debugging across large codebases