Quickstart

Goal: Upload a dataset, run a synthesis job, then download synthetic data and the quality/privacy report.

Syncora allows you to generate high-quality synthetic data in formats like JSONL, structured tables, time series, and image-label pairs—ideal for training AI models and simulations.

Want to learn about data generation from scratch? Head to the Core Concepts section to learn more.

Synthetic Data Generation

Let’s walk through how Syncora generates high-fidelity synthetic tabular data with an example.

Start by naming your project and uploading a sample dataset. Syncora supports both ,

• File Uploads

• Data Connectors

Upload a sample CSV and configure generation parameters like row count, diversity, and fixed values to control the structure and variability of your synthetic tabular dataset.

Generating Data

Once you click Launch Workflow, Syncora begins generating a synthetic version of your dataset based on your selected configurations—applying constraints, privacy settings, and sampling strategy to produce high-quality output. The result can be downloaded as a CSV or sent to an external connection. A detailed quality and privacy report is also generated if selected.

Syncora uses intelligent agents to generate your data step-by-step—starting with validation and structuring, then progressing through synthetic generation, quality checks, and privacy verification for a compliant and trustworthy dataset.

Preview a sample of the generated tabular data before finalizing. You can review structure, validate content quality, and go back to edit settings if needed before generating the full dataset.