amphi-ai/amphi-etl

visual data prep powered by python

What it solves

Amphi ETL simplifies the process of data preparation, reporting, and lightweight data transformation. It addresses the complexity of building data pipelines by providing a visual, low-code environment that generates clean, native Python code.

How it works

Users interact with a visual interface to design data pipelines, which the tool then converts into standard Python code using libraries like pandas and DuckDB. It can be run as a standalone application or as an extension within JupyterLab. Because it generates standard code, the resulting pipelines can be executed anywhere. It also supports extensibility, allowing users to define custom components using TypeScript to integrate specific logic or data sources.

Who it’s for

It is designed for data practitioners and developers who want to accelerate the development of data pipelines while maintaining the flexibility of native Python code. It is particularly well-suited for those who prioritize data privacy, as the tool can be self-hosted locally or on private servers.

Highlights

  • Visual, low-code interface for building data pipelines.
  • Generates native Python code using industry-standard libraries like pandas and DuckDB.
  • Fully self-hostable for complete data privacy and security.
  • Highly extensible through custom components defined in TypeScript.
  • Available as both a standalone app and a JupyterLab extension.

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