The data synthesis guides for software and AI teams

Featured guide

How to develop AI training datasets for compliance and performance

Explore strategies for balancing the compliance and performance of your AI training datasets. Learn how to manage data securely while optimizing accuracy and efficiency.

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Guide series
Data de-identification
Data synthesis
Test data management
Data privacy in AI
AI model training
Developer productivity
Tonic Structural how-tos
Tonic Textual how-tos
Tonic Fabricate how-tos
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Data privacy in AI

Best LLM security tools: features & more

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Tonic Textual
Data privacy in AI
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Data privacy in AI

Understanding LLM security risks (with solutions)

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Tonic Textual
Data privacy in AI
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Data privacy in AI

Understanding data redaction: methods, use cases, and benefits

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Tonic Textual
Data privacy in AI
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AI model training

What is retrieval augmented generation? The benefits of implementing RAG in using LLMs

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Tonic Textual
Tonic Validate
AI model training
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Test Data Management

The hidden value of test data: a case study on tech debt & business value

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Tonic Structural
Tonic Fabricate
Test Data Management
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Data de-identification

Data anonymization vs data masking: is there a difference?

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Tonic Structural
Data de-identification

Make your sensitive data usable for testing and development.

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