High-quality synthetic data

Learn about Gretel Navigator, our compound AI system, and Navigator Fine Tuning, our LLM-based AI system, designed to elevate your AI initiatives.

Modules

Overview

An organization’s data is often messy or incomplete, synthetic data can help fill in the gaps and ensure data quality meets model training standards. Generating accurate, high-quality synthetic data at scale is a core function of the Gretel platform. By leveraging Gretel, you can create domain-specific data tailored to fine-tune your models.

Gretel Navigator

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.

Resources

Gretel Navigator Fine Tuning

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.

Resources

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