AI-ready data, with privacy at the core

Unlock AI initiatives by maximizing your free-text assets through realistic data de-identification

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Achieve data privacy and AI optimization

Bring an end to critical bugs in production and accelerate your release cycles by fueling your staging and QA environments with data that mirrors the complexity of production.

In AI model training

Retain your data’s richness and preserve its statistics by replacing PII with synthetic values, to ensure optimal model training for LLM fine-tuning and custom models.

In RAG systems

Provide LLMs redacted data while optionally exposing the unredacted text to approved users. Automate pipelines to extract and normalize unstructured data into AI-ready formats.

In LLM workflows

Redact sensitive information prior to using it within LLM prompts to prevent sensitive values from ever entering the chatbot system.

In your lower environments

Accelerate data science based development with realistic test data that ensures data utility and data privacy throughout your lower environments

See Textual protect your data in real-time

Our proprietary NER models automatically identify entities in your text data to prevent potential privacy vulnerabilities in your AI development. Textual can de-identify any sensitive entities it detects via redaction or LLM synthesis.

Industry-leading sensitive data detection, redaction, and synthesis

Input

Connect Textual to your data store or upload files in any format via an intuitive UI or by feeding text directly into the Textual SDK.

Seamlessly connect to your data to ingest any file format into Textual.

Extract

Automatically extract your free-text data and detect over thirty sensitive entity types with Textual’s multilingual NER models.

Automatically extract named entities using Textual’s proprietary NER models to create metadata and knowledge graphs that improve RAG system performance.

Protect

Leverage granular controls to de-identify your data consistently, either through redaction or realistic synthesis, replacing sensitive values while maintaining semantic integrity.

Optionally redact or synthesize replacement values for NER-detected sensitive data, if privacy is a concern.

Deliver

Output your protected data in its original file format or in a standardized, markdown format optimized for model training and RAG systems.

Support for all your data formats

90% of enterprise intelligence is locked up in files across the business. With Textual, you can unlock unstructured enterprise data however and wherever it’s stored:

.csv

.txt

XML

.pdf

HTML

JSON

.pptx

.docx

.png

.jpeg

.xls

+ more