Tonic Textual guide

Tonic Textual provides a single tool to allow you to put your file-based data to work for you.

The Textual pipeline option allows you to prepare unstructured text for use in an LLM system. Textual extracts the text from each file and then produces Markdown-formatted output. You can optionally replace sensitive values in the output, to prevent data leakage from your LLM.

You can also use Textual datasets to redact sensitive values, to produce files in the same format to use for development and training. Each original file becomes an output file in the same format, with the sensitive values replaced.

Textual workflows

Getting started with Textual

Sign up for a Textual account. Create your first pipeline.

Pipelines workflow - LLM preparation

Use Textual to prepare file content for use in an LLM system.

Datasets workflow - File redaction and synthesis

Use Textual to replace sensitive values in files.

Textual SDK and Snowflake Native App

Datasets and redaction

Use the Textual Python SDK to redact text and manage datasets. Review redaction requests in the Request Explorer.

Pipelines and parsing

Use the Textual Python SDK to parse text and manage pipelines.

Snowflake Native App

Use the Snowflake Native App to redact values in your data warehouse.

Need help with Textual? Contact [e-mail].