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Demo: fine-tuning LLMs with Tonic Textual

In this blog post, Tonic.ai’s Head of AI, Ander Steele, walks through a live demo of how Tonic Textual can be used to automatically de-identify protected health information (PHI) within unstructured data—making it safe and compliant for fine-tuning large language models (LLMs).

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

Tonic.ai editorial
Tonic.ai editorial
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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

How Alegeus Shortens Sprints to Deploy Healthtech at Speed with Tonic

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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

Getting the data you want out of JSON with JSONPath

Technical deep dive
Technical deep dive
Tonic Structural

Database subsetting is not a piece of cake, so we baked Condenser 2.0 just for you

Technical deep dive
Technical deep dive
Tonic Structural

Masquerade: a Postgres proxy to mask data in realtime

Technical deep dive
Technical deep dive
No items found.

How to generate realistic test data with Faker

Technical deep dive
Technical deep dive
Tonic Structural
Tonic Fabricate

Build better and faster with quality test data today.

Unblock data access, turbocharge development, and respect data privacy as a human right.
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.