Gretel Navigator is the world’s first compound AI system designed to create high-quality tabular datasets using natural language or code. With Navigator, you can iteratively create, edit, and augment tabular datasets with just a simple prompt.

Gretel Navigator Fine Tuning is an AI system that combines a Large-Language Model pre-trained on tabular datasets with schema-based rules. It can train on datasets of various sizes and generate synthetic datasets with unlimited records. Navigator Fine Tuning excels at matching correlations (both within a single record and across multiple records) and distributions in its training data across various tabular modalities, including numeric, categorical, free text, JSON, and time series values.

Transform v2 is a general-purpose programmatic dataset editing tool. It allows users to easily detect arbitrary entities specific to their business, and define custom transformation rules to generate data matching the exact format and logic they need. This feature not only extends Transform’s already robust de-identification capabilities, but also makes Transform v2 adaptable enough beyond de-identification, to cover most dataset pre and post processing use cases.

Gretel ACTGAN is an adversarial model that is designed to generate tabular data with advanced features like conditional data generation. It performs well with primarily numeric datasets, high column counts, and unique categorical fields.