Tonic.ai Blog | Synthetic Data Insights & Engineering

Training effective models without the annotation budget

Learn how to bypass costly annotation workflows by using LLM-generated labels and lightweight fine-tuning to build high-quality NER models with minimal human input.

Using data upsert to optimize test data management

Test data management

Tonic Structural

Elevating RAG system reliability: integration testing with Tonic Validate & LlamaIndex

Technical deep dive

Tonic Validate

How 2024 will impact DevOps teams

Tonic.ai editorial

Tonic Structural

Tonic Textual: document redaction to de-identify PDFs and Word docs

Data de-identification

Data privacy

Generative AI

Tonic Textual

How 2024 will impact quality engineering teams

Tonic.ai editorial

Test data management

Tonic Structural

Redacting sensitive free-text data: build vs buy

Technical deep dive

Tonic Textual

Introducing Tonic Textual: redact and synthesize sensitive free-text data

Product updates

Data de-identification

Generative AI

Data privacy

Data synthesis

Tonic Textual

RAG evaluation series: validating the RAG performance of LangChain vs Haystack

Technical deep dive

Tonic Validate

Unlocking secure data utility: the Tonic.ai and Databricks partnership and integration

Product updates

Tonic Structural

RAG evaluation series: validating the RAG performance of OpenAI vs LlamaIndex

Technical deep dive

Tonic Validate

RAG evaluation series: validating OpenAI Assistant’s RAG performance

Technical deep dive

Tonic Validate

How to mask sensitive data in files, from CSV to JSON

Data de-identification

Data privacy

Test data management

Tonic Structural

Expert insights on synthetic data

Training effective models without the annotation budget

Blog posts

Using data upsert to optimize test data management

Elevating RAG system reliability: integration testing with Tonic Validate & LlamaIndex

How 2024 will impact DevOps teams

Tonic Textual: document redaction to de-identify PDFs and Word docs

How 2024 will impact quality engineering teams

Redacting sensitive free-text data: build vs buy

Introducing Tonic Textual: redact and synthesize sensitive free-text data

RAG evaluation series: validating the RAG performance of LangChain vs Haystack

Unlocking secure data utility: the Tonic.ai and Databricks partnership and integration

RAG evaluation series: validating the RAG performance of OpenAI vs LlamaIndex

RAG evaluation series: validating OpenAI Assistant’s RAG performance

How to mask sensitive data in files, from CSV to JSON

Build better and faster with quality test data today.