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How to de-identify insurance claims and documents with Tonic Textual

Insurance claims and documents contain sensitive PII that block these sources of data for use in AI and ML training initiatives. Tonic Textual can be used to de-identify sensitive entities, while retaining important context.

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How to generate safe, useful test data for Amazon Redshift

Technical deep dive
Technical deep dive
Tonic Structural

5 traditional approaches to generating test data

Technical deep dive
Technical deep dive
Tonic Structural
Tonic Fabricate

Why I joined Tonic.ai: A software engineer's perspective

Tonic.ai editorial
Tonic.ai editorial
No items found.

Creating realistic, secure test data for Databricks

Technical deep dive
Technical deep dive
Tonic Structural

Reverse engineering your test data: It’s not as safe as you think it is

Test data management
Test data management
Data de-identification
Data privacy
Tonic Structural

Why I joined Tonic.ai: A product manager's perspective

Tonic.ai editorial
Tonic.ai editorial
No items found.

Spring 2021 product update

Product updates
Product updates
Tonic Structural

How to create realistic test data for PostgreSQL

Technical deep dive
Technical deep dive
Tonic Structural
Tonic Fabricate

NoSQL vs SQL: what you need to know

Technical deep dive
Technical deep dive
No items found.

Using Docker to manage your test database(s)

Technical deep dive
Technical deep dive
Tonic Structural

Mockaroo and Tonic.ai: Partners in mock data generation

Tonic.ai editorial
Tonic.ai editorial
Tonic Structural

Your data is safe — math guarantees it!

Technical deep dive
Technical deep dive
Tonic Structural
Accelerate development with high-quality, privacy-respecting synthetic test data from Tonic.ai.Boost development speed and maintain data privacy with Tonic.ai's synthetic data solutions, ensuring secure and efficient test environments.