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AutoSage has a small set of concepts. Once you know how they nest, the whole platform is easy to navigate.

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The hierarchy

Organization
  └── Environment            (dev / staging / production)
        └── Tenant           (credits, quotas, data isolation)
              └── Knowledge base
                    ├── Documents        (the RAG corpus)
                    ├── Database connections
                    ├── Prompts          (persona, instructions, custom prompt)
                    ├── Agents           (saved, deployable configurations)
                    └── Chats            (conversations)
Each resource has its own deletion behavior. Environment and tenant deletion remove their contained data, while deleting a knowledge base removes its content and archives dependent agents rather than deleting their history. Review the relevant resource page before deleting production data.
Every knowledge base belongs to exactly one tenant, and retrieval stays within its private corpus. Agent sharing can pass another agent’s final answer back to the caller, but it does not expose or merge the other knowledge base’s documents.

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The main objects

Your top-level account — the business or team. It owns billing, members and their roles, and one or more environments. When you create an organization, AutoSage automatically sets up a default environment and tenant so you can start immediately.
An isolation context within an organization, such as dev, staging, or production. API keys are scoped to a single environment — a key can never reach data in another environment. Use separate environments to keep test data away from production.
A resource owner that holds its own credit pool and quotas (max knowledge bases, documents, and storage). Tenants are the data-isolation unit. In a multi-customer product, you typically create one tenant per customer so their usage and data stay separate.
The workspace that ties everything together: uploaded documents, database connections, the prompts that shape the assistant’s voice, the agents built on it, and the chats that run against it. Most day-to-day configuration happens at the knowledge base level.
A saved, versioned configuration — a goal, instructions, a model, and a set of tools and skills — that runs on a knowledge base. Agents can be run interactively, called through the API, or triggered on a schedule. See Agents.
A single conversation. Chats stream responses, keep long-running context through compaction, and can be shared read-only. Both dashboard conversations and agent runs use the same underlying chat engine.
Durable facts an assistant can recall across separate conversations — preferences, decisions, and context you want it to remember. Memory is optional and configured per tenant and per knowledge base. See Memory.

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How a question gets answered

When someone sends a message, AutoSage assembles an answer from several grounded sources:
1

Retrieve from documents

The agent searches the knowledge base for the most relevant passages and cites them.
2

Query connected data

If the knowledge base has database connections, the agent can run read queries and chart the results.
3

Use tools and connected apps

The agent can call connected apps, custom tools, MCP servers, or delegate to another agent.
4

Recall memory

If memory is enabled, relevant durable facts from past conversations are added to the context.
5

Answer

The model produces a grounded response with citations when retrieval finds supporting sources. Streaming exposes live progress and final content.

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Where to go next

Set up a knowledge base

Upload documents and shape the assistant’s voice.

Build an agent

Give it a goal, tools, and optionally a schedule.