> For the complete documentation index, see [llms.txt](https://k-ai.gitbook.io/knowledge-ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://k-ai.gitbook.io/knowledge-ai/sources-and-ingestion/sources-ingestion.md).

# Overview

Sources & ingestion is how documents enter the K-AI Platform. K-AI does not require centralising the document estate — it addresses sources where they live, ingests them incrementally, preserves their native ACLs, and indexes them into the Semantic Document Layer.

## What's in this section

* **Connectors** — supported source types, one sub-page per connector. SharePoint, Confluence, Notion, Google Drive, Azure Blob Storage, Snowflake Stage, ServiceNow, Mayday, Stonly, generic HTTP, and the web crawler are documented in the section navigation. Start with the [SharePoint connector](/knowledge-ai/sources-and-ingestion/connectors/sharepoint.md); the others follow the same shape.
* **Document state machine** — the lifecycle of a document from registration to indexed. See [Document state machine](/knowledge-ai/sources-and-ingestion/document-state-machine.md).
* **Indexation pipeline** — what runs between source and Semantic Document Layer. See [Indexation pipeline](/knowledge-ai/sources-and-ingestion/indexation-pipeline.md).
* **Indexation control** — each instance page of the K-AI Studio portal shows indexing statistics and, for users allowed to manage the instance, offers **Partial indexation** and **Retry parsing errors**.

## Architectural placement

This section covers Layers 1 (Sources) and 2 (Ingestion & Indexing) of the [5-layer architecture](/knowledge-ai/the-k-ai-platform/architecture.md). Layer 3 (Semantic Document Layer) is the [Neural Semantic Graph](/knowledge-ai/the-k-ai-platform/neural-semantic-graph.md). Layers 4 (Governance & Quality) and 5 (Exposure) are covered by [K-AI Audit](/knowledge-ai/k-ai-audit/audit.md) and [K-AI MCP](/knowledge-ai/k-ai-mcp/mcp.md) respectively.

## Auth

Indexation is driven from the K-AI Studio portal under your browser session — see [Cookies](/knowledge-ai/authentication/cookies.md). Ingested content is consumed through [K-AI MCP](/knowledge-ai/k-ai-mcp/mcp.md) and the [Audit API](/knowledge-ai/k-ai-audit/audit.md); for automation, use an [Organization API key](/knowledge-ai/authentication/organization-api-keys.md).

## Next steps

1. Pick a connector (e.g. [SharePoint](/knowledge-ai/sources-and-ingestion/connectors/sharepoint.md)).
2. Follow indexation progress on the instance page of the K-AI Studio portal — see [Document state machine](/knowledge-ai/sources-and-ingestion/document-state-machine.md).
3. Query the indexed content through [K-AI MCP](/knowledge-ai/k-ai-mcp/mcp.md).