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Aumo - Introduction

Create and Manage AI Assistants with RAG and Total Privacy​

  • Connect multiple knowledge sources (Google Drive, Confluence, Jira, and more)
  • Create custom assistants with multiple AI models (OpenAI, Anthropic, Google, and others)
  • Unified interface to manage your entire AI infrastructure
  • Total privacy - your data is never used to train external models
  • RAG (Retrieval-Augmented Generation) for precise answers based on your knowledge

How to Use Our Tool​

You can use Aumo through two main interfaces. Both offer full access to the platform but with different focuses. Choose the option that best fits your needs:

Admin PlatformChat Platform
Use CaseManage organizations, projects, members, credentials, and assistants
Who Uses It?Administrators, Managers, DevOps
Key Features• Manage assistants and settings
• Connect knowledge sources
• Manage credentials and providers
• Configure MCP servers
• Administer members and permissions
• Admin dashboard for monitoring

Admin Platform​

Quick Start - Admin Platform​

Step 1: Access the Admin Dashboard​

  1. Log in to the platform
  2. Navigate to the admin dashboard

Step 2: Set Up an AI Provider​

  1. Go to Providers → Create Provider
  2. Select the provider (OpenAI, Anthropic, Google, etc.)
  3. Configure your credentials

Step 3: Create a Knowledge Source​

  1. Go to Knowledge Sources → Create Source
  2. Connect Google Drive, Confluence, or another source
  3. Configure indexing

Step 4: Create an Assistant​

  1. Go to Assistants → Create Assistant
  2. Select the AI model
  3. Configure knowledge collections
  4. Define the workflow

📖 Next Steps:

Chat Platform​

Quick Start - Chat Platform​

Step 1: Access the Chat​

  1. Log in to the platform
  2. Navigate to the chat interface

Step 2: Select an Assistant​

  1. Choose an available assistant
  2. The assistant will already have access to the configured knowledge

Step 3: Start a Conversation​

  1. Type your question or message
  2. The assistant will respond using the available knowledge

📖 Next Steps:

🔑 Key Concepts​

Before getting started, it’s useful to understand some key concepts:

Assistants​

Assistants are AI agents configured with specific models, knowledge sources, and custom workflows.

Knowledge Sources​

Knowledge sources are connections to data repositories (Google Drive, Confluence, Jira, etc.) that are indexed and made available to the assistants.

Knowledge Collections​

Collections organize multiple knowledge sources into logical groups, facilitating management and assignment to assistants.

Providers​

Providers are AI services (OpenAI, Anthropic, Google, etc.) that supply the language models used by the assistants.

MCP Servers​

MCP (Model Context Protocol) servers allow for the integration of advanced functionalities and external tools into the assistants.

More details​

📚 Additional Resources​

🆘 Need Help?​

Last updated on by gabriel.ambrozini