---
title: Overview | Adaption
description: Understand what Adaptive Data produces and how data moves from import through adaptation and evaluation.
---

Adaptive Data analyzes the structure of your source data, then adapts and optimizes it into a model-ready dataset for AI training.

## What you can build

- **Instruction datasets** — prompts paired with expected completions for supervised fine-tuning
- **Preference pairs** — two completions compared to indicate which is better, for preference-based training

## How it works

Adaptive Data runs through six stages:

1. **[Import](/adaptive-data/create-a-dataset/index.md)** — bring in data from a local file, Hugging Face, or Kaggle.
2. **[Expand](/adaptive-data/configure-adaptive-data#expand-across-languages-and-locales/index.md)** — optionally translate the data or localize it for a language and country.
3. **[Map columns](/adaptive-data/select-columns/index.md)** — identify prompt, completion, context, image, or chat data.
4. **[Apply recipes](/adaptive-data/configure-adaptive-data#apply-recipes/index.md)** — optionally deduplicate or rephrase prompts and generate reasoning traces.
5. **[Set brand controls](/adaptive-data/configure-adaptive-data#configure-brand-controls/index.md)** — optionally control length, safety, grounding, tone, and other Blueprint instructions.
6. **[Run](/api/python/resources/datasets/methods/run/index.md) and [evaluate](/adaptive-data/evaluate-dataset-quality/index.md)** — start adaptation, then compare quality signals for the source and adapted data.

## Supported inputs

- **File formats**: CSV, JSON, JSONL, Parquet, PDF, DOCX, PPTX, XLSX, HTML, ZIP, and TXT
- **Hugging Face**: point at a dataset URL
- **Kaggle**: point at a dataset page URL

Start with the [Adaptive Data quickstart](/adaptive-data-quickstart/index.md), or browse the complete [API reference](/api/python/index.md).