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AIConsole
Workflows
Free

AIConsole

Open-source desktop AI editor and multi-agent platform to automate local workflows, execute code, and manage tasks using personalized materials and custom AI agents.

Rating
0
Reviews
0
Upvotes
3 months ago
Listed
Open Source
Workflow Automation
AI Agents
RAG
Productivity
Desktop App
Developer Tools
Python
Multi-Agent Systems
Privacy-Focused
Tool information
Provider
10Clouds
Platforms
Windows
macOS (Intel)
macOS (ARM)
Linux
Languages
English
API Available
Yes
Added to directory
3 months ago
Last updated
about 2 months ago
Rating
Not available
Pricing
Free

About AIConsole

What the tool does and who it's for

AIConsole is an open-source, desktop-based AI editor and multi-agent orchestration platform designed to automate complex professional workflows. Unlike standard chat interfaces, it operates locally on your machine, allowing it to execute code, manage files, and interact with your system directly. It uses a unique 'Materials' system—plain-text documents and Python snippets—that teaches the AI how to handle specific tasks, such as sending iMessages, managing calendars, or processing legal documents. By leveraging a multi-agent Retrieval-Augmented Generation (RAG) architecture, AIConsole provides precise task execution that improves as you add more context and notes, all while ensuring data privacy by communicating only with your chosen LLM APIs.

Key capabilities

Local Code Execution: Run Python scripts and system commands directly from the console to automate local tasks.
Materials System: Use plain-text notes and manuals to teach the AI specific domain knowledge or personal workflows.
Multi-Agent Orchestration: Deploy specialized agents (e.g., Document Handover, Contract Comparison) that work together.
Privacy-First Architecture: Your data stays on your machine; the tool only transmits necessary context to your selected LLM API.
Universal LLM Integration: Connect to OpenAI, Azure OpenAI, Anthropic, or any OpenAI-compatible self-hosted model.
Persistent Learning: Describe a task once in a 'Material' file, and the AI remembers how to execute it indefinitely.
Agent Customization: Define and enable/disable specific agents via .toml configuration files within your project directory.
Expert-Level RAG: Leverages a precise multi-agent retrieval system that outperforms standard vector database approaches for task steps.

Pricing

Free — plans below

Open Source

Most popular

0

  • Full source code access
  • Local execution on Windows/Mac/Linux
  • Unlimited custom Materials
  • Multi-agent support
  • Connect your own API keys

Enterprise

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  • Managed deployment on Azure
  • Custom agent development
  • Enterprise-grade security and compliance
  • Advanced auditing and logging
  • Priority support and integration services

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