PrettyWhale.ai

A PrettyWhale.ai license is required: The extension is free to install but running a generation needs an active license, which we set up with you. Talk to us if you don't have one yet.

What is PrettyWhale.ai?

PrettyWhale.ai is an AI-powered solution that turns a sample data file into a complete, production-ready data ingestion pipeline, in minutes. Instead of writing boilerplate parsing code, validation logic, and documentation by hand, you upload a sample file and PrettyWhale.ai generates everything your team needs to ship a reliable pipeline from day one.

PrettyWhale is built for data engineers and data teams who spend too much time writing repetitive ingestion code. You provide a sample file, JSON, CSV, or another supported format, and PrettyWhale.ai’s Small Language Model (SLM) analyzes the structure, suggests transformations, and generates a complete artifact set: ingestion script, unit tests, data quality rules, schema definition, and pipeline documentation.

The platform is designed around a workflow that mirrors how experienced data engineers think about building a pipeline, just without the manual effort. Whether you’re ingesting customer records, event streams, or product data, PrettyWhale.ai produces consistent, maintainable code that follows industry standards and is ready for your production environment.

Features

• Generate production-ready ingestion and integration pipeline code from your data sample.
• Get data transformation to clean and refine each data of your source.
• Obtain matching schemas and unit tests alongside the generated code.

How it works

1. Install the extension.
2. Click the PrettyWhale.ai icon in the left bar and sign in with your account: a browser window opens to complete authentication.
3. Then open the PrettyWhale.ai panel and point it at a sample of your source, a CSV or a JSON extract for example.
4. Pick your target language, the few settings that apply and run the flow !
5. A few minutes after, the project (all the needed artifacts) lands in your workspace, ready to open and execute.

What you get

A flow returns a working data pipeline:

your-pipeline/
├── pipeline.py          entry point
├── config.yaml          run configuration
├── schema.json          JSON Schema describing the output contract
├── lib/                 one processor per data transformation
├── tests/               pytest suite covering the processors and the schema
├── requirements.txt     pinned dependencies
└── README.md            what the pipeline does and how to run it

Clone it, read it, run it, commit it. There is no runtime to license and no platform to stay inside. The code is yours, and it deploys wherever your other code deploys.

Support

Questions or issues? Contact us via prettywhale.ai/contact.

We'd love to hear from you!