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Deliver exceptional customer experiences by responding to job changes of your most valuable buyers with the right action at the right time.

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With Airbyte the Salesloft users can integrate their data to destinations including cloud data warehouses, like Amazon Redshift, Snowflake, and BigQuery, or to on-premises storage to be exploited through AI analytics. The pipeline process is known as "extract, load, transform", usually referred to as either "ETL" or "ELT", depending on the order in which the data is being moved and processed. We're building an open-source data integration platform, focusing mostly on the EL part.

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With Airbyte any Salesloft user can manage data and consolidate it into a single data lake to generate global reports or integrate with different destinations including cloud data warehouses lakes, and databases or to on-premises storage to be exploited through AI analytics.

Synchronizing data from one data database to another is complicated. Often the net result is extremely long cycles for development and deployment that takes several months to complete and is costly to maintain. Airbyte makes it easier to overcome these constraints.

To use Airbyte Open source you should install the standalone app to your computer, visit our docs to get the instructions.

To use Airbyte Cloud, you can sign up and try it for free. 




Build custom connectors

 Create a custom source or destination connector using our Connector Development Kit within an hour. 

Edit existing connectors

 25% of our users edit Connectors to best fit their use case. Make the necessary changes like adding custom fields without building from scratch. 

Customize our platform

 Whether it's making deployment changes, adding security measures, or even writing your own unique workers - customizing Airbyte is as easy as forking the code. As an open-source project, all contributions are welcome. 

Shared Data

Start analyzing your Salesloft data in minutes with the right data transformation: 

  • Full control over the data. You select the data you want to replicate, and this for each destination you want to replicate your Intercom data to.
  • Normalized schemas. You can opt for getting the raw data, or to explode all nested API objects in separate tables.
  • Custom transformation via dbt. You can add any dbt transformation model you want and even sequence them in the order you need, so you get the data in the exact format you need at your cloud data warehouse, lake or database.