SynData
Generate High-Quality
Synthetic Data
Data for tomorrow, generated today.Transform your PDF documents into structured question-answer pairs using state-of-the-art language models
Open for contributions! Join us and help shape the future of synthetic data.
Open Source & Contributions
Syndata is open source and open for contributions! Whether you want to fix bugs, add features, improve documentation, or share feedback, your input is valued.
Contribute on GitHubKey Features
PDF Processing
Upload and process PDF documents to extract meaningful content chunks
AI-Powered Generation
Generate synthetic question-answer pairs using advanced LLM models
Easy Export
Download generated data in CSV format for immediate use
Use Cases
RAG Evaluation
Assess and optimize Retrieval-Augmented Generation pipelines by generating targeted synthetic queries and answers for robust evaluation.
Model Benchmarking
Compare the performance of different LLMs using custom synthetic datasets tailored to specific domains and tasks.
Data Augmentation
Enrich real-world datasets with diverse synthetic samples to improve model generalization and reduce overfitting.
QA System Testing
Stress-test question-answering systems with edge-case and domain-specific synthetic Q&A pairs.
Enterprise Knowledge Validation
Validate and audit internal knowledge bases by simulating user queries and expected responses from enterprise documents.
Educational Content Creation
Automatically generate quizzes, study guides, and practice questions from textbooks and course materials for e-learning platforms.
How It Works
Upload PDF
Upload your PDF document to begin processing
Configure Settings
Set parameters like model, chunk size, and data points
Generate Data
AI processes your document and creates synthetic Q&A pairs
Download Results
Export your generated data as CSV for immediate use