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Accelerate and improve LLM and RAG development with the secure data lakehouse for AI focused on unstructured data management

Maximize data science, minimize data preparation
Extract

Maximize data science, minimize data preparation

Pre-process unstructured data at scale and streamline AI development by converting your unstructured data into standard formats ingestible by LLMs and RAG systems.

Maximize data science, minimize data preparation
Enrich

Elevate RAG performance and accuracy

Leverage Textual’s NER models to enrich your data with high-quality metadata, pushing beyond vector similarity with customized entity tags.

Protect sensitive and proprietary data
Govern

Protect sensitive and proprietary data

Automatically detect, redact and synthesize sensitive information, like PII and PHI, in unstructured documents to prevent model memorization and sensitive data leakage.

Integrate and manage LLM app deployments
Deploy

Connect your data to downstream AI processes

Integrate with the leading embedding models, vector databases, and AI developer platforms for RAG and fine-tuning.

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.
Build production-grade unstructured data pipelines for AI systems in minutes
1
Connect
Seamlessly connect to your data to ingest any file format into Textual.
Seamlessly connect to your data to ingest any file format into Textual.
Seamlessly connect to your data to ingest any file format into Textual.
2
Extract
Automatically extract named entities using Textual’s proprietary NER models to create metadata and knowledge graphs that improve RAG system performance.
Extract
Automatically extract named entities using Textual’s proprietary NER models to create metadata and knowledge graphs that improve RAG system performance.
3
Protect
Optionally redact or synthesize replacement values for NER-detected sensitive data, if privacy is a concern.
Protect
Optionally redact or synthesize replacement values for NER-detected sensitive data, if privacy is a concern.
4
Transform
Transform unstructured data into structured formats to streamline embedding, ingestion into vector databases, and fine-tuning and pre-training machine learning models.
Transform
Transform unstructured data into structured formats to streamline embedding, ingestion into vector databases, and fine-tuning and pre-training machine learning models.
Image Support for all your data formats

Support for all your data formats

90% of enterprise intelligence is locked up in files across the business. With Textual, you can now unlock unstructured enterprise data however and wherever it’s stored.
.csv
.txt
.tiff
.pdf
.parquet
JSON
.pptx
.docx
.png
.jpeg
.xls
+ more

Available wherever your data lives

Burn down your cloud commitments by procuring Tonic Textual via the AWS Marketplace, Google Cloud Platform Marketplace, or Snowflake Marketplace

AWS marketplace
Google Cloud Platform Marketplace
Snowflake Marketplace
Featured
Resources
Learn more about Tonic Textual by way of technical deep dives, guide, and webinars.
See all
The Role of NER in GDPR Compliance and Beyond
Generative AI
Guide to data privacy compliance for financial institutions
Data synthesis
Understanding automated data redaction
Data Masking
The Role of NER in GDPR Compliance and Beyond
Generative AI
Security for Tonic.ai cloud products
Tonic how-tos

Connect your enterprise data to LLMs with Tonic Textual today.

Unlock the power of generative AI while safeguarding your most important data.