> ## Documentation Index > Fetch the complete documentation index at: https://docs.trymaitai.com/llms.txt > Use this file to discover all available pages before exploring further. # Dataset Creation > How to capture and generate data for fine-tuning The foundation of any fine-tune is the data. You can build your datasets using three primary methods in Maitai: Dataset Creation ### Production Traffic Promote real-world interactions directly from the **Observe** view into a dataset. This ensures your model is trained on the actual distributions of your users' requests. ### Manual Upload Import your existing "gold standard" data via CSV or JSON. This is ideal for bootstrapping a model when you already have a verified corpus of high-quality interactions. ### Synthetic Generation Use the **Synthetic Conversation Tree (SCT)** visualizer to map out the logic of your application and generate thousands of unique, structured training examples. This is powerful for covering edge cases that haven't occurred in production yet. ## Next * Prepare and refine your data: [Dataset Preparation](/build/models/dataset_preparation) * Full end-to-end walkthrough: [Fine-tune a Model](/examples/fine_tuning)