Automatically create code, tests, and documentation for your data workflows.
Identification sample analysis
Import a sample file (JSON, CSV, etc.) so PrettyWhale.ai can automatically analyze its structure, detect fields, and understand how your data is organized. No manual setup required.
Scope of data
PrettyWhale.ai generates a detailed analysis of your data, highlighting each field with examples and insights. You can then select only the fields you want to keep, giving you full control over your dataset.
Transform suggestion
Based on the analysis, PrettyWhale.ai suggests relevant transformations such as normalization, formatting, and data cleaning. You can easily review, adjust, remove, or add your own transformations to match your exact requirements.
Suggestion and selection
Enhance your dataset by connecting to external data sources. PrettyWhale.ai helps you enrich your data with additional context, making it more complete and valuable for downstream use.
Code and deliverables
PrettyWhale.ai generates everything you need: ingestion code, documentation, schemas, and unit tests. The code is validated and ready to be deployed in production, saving hours of manual work.
What if AI could speed up the most technical, costly, time-consuming, and tedious part of data projects? We picture data projects as analysis and dashboards. In practice, most of the time goes somewhere else: collecting the sources, understanding their structure, transforming, validating, making them usable. This work is essential, but it’s often time-consuming, complex, and repetitive. To tackle this challenge, Moove-SI is partnering with PrettyWhale.ai 🐋 PrettyWhale.ai develops AI enginee
Four families of AI coding tools, separated by what they actually hand you. A taxonomy you can use to choose, including when the answer is not code generation.
For more than thirty years, the economic model of IT services companies (ESNs in France) has relied on a simple equation: selling human time. The arrival of AI profoundly changes this equation. When an engineer can produce in a few hours what previously required several days, a question becomes inevitable: Should the client continue to buy time or start buying results? The paradox is striking: The more productive an IT services company becomes thanks to AI, the fewer days it theoretically needs
In many Data projects, the terms ingestion and integration are used as synonyms. Yet, they designate two radically different realities. And this confusion is at the root of a large part of the cost overruns, delays, and quality problems that companies face today. Ingestion code: the foundation The ingestion code is responsible for collecting, controlling, standardizing, and preparing data as soon as it enters the information system. It is what: * reads files, APIs, databases, or externa
