Differentially Private Synthetic Text Generation with Gretel: Making Data Available at Scale (Part 1)

Gretel is a platform that enables organizations to generate synthetic text data with differential privacy guarantees, making sensitive natural language data available for various use cases while maintaining individual privacy. The platform uses state-of-the-art large language models (LLMs) and applies differential privacy during model fine-tuning through the DP-SGD algorithm. Gretel's synthetic text generation approach is particularly impactful in industries like finance, healthcare, and customer support, where handling sensitive data securely is crucial. The platform provides a reliable measure of data utility without compromising private data using its SQS (Synthetic Quality Score) evaluation metric.