> ## Documentation Index
> Fetch the complete documentation index at: https://docs.rippit.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Connect data

> Bring conversations and business data into Rippit from a built-in integration, Snowflake or the Bulk API.

Every way of connecting data ends the same way: a **data table** in Rippit that keeps syncing. Once it's there, you [query it](https://docs.rippit.com/api-reference/query/overview.md), run ad hoc bulk AI analysis in [worksheets](https://docs.rippit.com/api-reference/worksheets/overview.md), and create ongoing [AI tables](https://docs.rippit.com/enrich/ai-tables.md).

## Pick a source

| Source | Use it for | Sync |
| - | - | - |
| [Built-in integrations](https://docs.rippit.com/api-reference/connect/integrations/overview.md) | Helpdesks, call recorders and chat tools such as Zendesk, Intercom and Gong | Continuous |
| [Snowflake](https://docs.rippit.com/api-reference/connect/snowflake/overview.md) | Tables already in your warehouse: accounts, orders, usage | Every few hours, on a schedule you set |
| [Bulk API](https://docs.rippit.com/api-reference/connect/bulk/overview.md) | Conversations or tables from systems with no integration | Each time you upload |
| [Rippit CLI](https://docs.rippit.com/cli.md) | A one-off CSV file | Once, into a worksheet |

## Linking data to conversations

Tables join to conversations on a `conversation_id` column. Send ticket metadata or the orders a customer placed alongside the conversation itself, then filter and analyze them together.


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