Expert insights on synthetic data

The latest

De-identifying and synthesizing healthcare PDFs of patient lab reports for model training and Expert Determination

PDFs are the hardest healthcare data to de-identify. Here is how Tonic Textual identifies PHI in lab reports and synthesizes realistic replacements for Expert Determination.

Blog posts

Top 5 risks of not redacting sensitive business information when machine learning

Data privacy
Data privacy
Tonic Textual

Tonic.ai product updates: March 2024

Product updates
Product updates
Tonic Structural
Tonic Textual
Tonic Validate

De-identifying Salesforce data for testing and development. Tonic Structural now connects to Salesforce

Product updates
Product updates
Tonic Structural

De-identifying test data: K2View’s entity modeling vs Tonic’s native modeling

Test data management
Test data management
Data de-identification
Technical deep dive
Tonic Structural

Tonic Validate is now on GitHub Marketplace! (Part 2)

Product updates
Product updates
Generative AI
Tonic Validate

Tonic Validate is now available on GitHub Marketplace!

Product updates
Product updates
Generative AI
Tonic Validate

Tonic.ai product updates: February 2024

Product updates
Product updates
Tonic Structural
Tonic Textual
Tonic Validate

RAG evaluation series: validating the RAG performance of OpenAI vs CustomGPT.ai

Technical deep dive
Technical deep dive
Tonic Validate

Redacting sensitive text data in JSON with Tonic Textual

Data de-identification
Data de-identification
Data privacy
Generative AI
Tonic Textual

RAG evaluation series: validating the RAG performance of OpenAI’s RAG Assistant vs Google’s Vertex Search and Conversation

Technical deep dive
Technical deep dive
Tonic Validate

RAG evaluation series: validating the RAG performance of Amazon Titan vs Cohere using Amazon Bedrock

Technical deep dive
Technical deep dive
Tonic Validate

Leveling up your test environments with OCI artifacts

Technical deep dive
Technical deep dive
Tonic Structural