Tonic Reviews

What do you like best about Tonic.ai?What I like best about Tonic.ai is one of its products, Tonic Textual, and how effectively it identifies and anonymizes entities without breaking context. This is critical when working with large volumes of unstructured text. What do you dislike about Tonic.ai? Recommendations to others considering Tonic.ai?The controls are intuitive, the output is consistent, and the overall experience feels reliable rather than experimental. From a practical standpoint, it helps teams move forward with confidence on privacy without compromising the value of the data. That balance is what stands out most.What problems is Tonic.ai solving and how is that benefiting you?At times, the tool can lean toward over-masking, but that is generally acceptable from a privacy standpoint. From our perspective, over-masking is far preferable to under-masking, especially when handling sensitive text.

What do you like best about Tonic.ai?This tool excels at generating realistic and safe test data that closely resembles our actual production database. It has been incredibly helpful for debugging and testing, allowing us to work without ever putting sensitive customer PII at risk.What do you dislike about Tonic.ai?Setting up and configuring the system can be quite complicated, particularly when dealing with our more complex database schemas. Additionally, the cost is rather steep, making it difficult for smaller teams to find it justifiable.What problems is Tonic.ai solving and how is that benefiting you?Tonic.ai addresses a fundamental challenge for developers: the need for realistic data to test code, without resorting to actual customer production data due to significant security and privacy concerns. Creating "dummy" data by hand is not an effective alternative, as it is both time-consuming and unlikely to uncover real-world issues. For me, the advantage is substantial—Tonic provides a secure, anonymized dataset that closely mirrors our production data.

What do you like best about Tonic.ai?Tonic takes the guesswork out of providing data for engineers to use during debugging etc. We wrote a simple automation that runs Tonic every day, and as a result our developers have up-to-date info to work with that is largely set-and-forget.What do you dislike about Tonic.ai?There's no Okta integration, and the ability to configure user permissions is tied to their most-expensive Enterprise tier, but these aren't dealbreakers.What problems is Tonic.ai solving and how is that benefiting you?Tonic lets us provide near-production data to our developers, which shortens cycle time for diagnosing technical issues while keeping PII away from developers outside of exceptional circumstances. Tonic's API means we can automate it, so we can invoke a sanitization run from Slack, from a scheduled Lambda, etc. It turns it into a set-and-forget tool that only needs to be touched when the database schema changes.

What do you like best about Tonic.ai?We used Tonic Textual AI for data anonymization and were impressed by how easy it was to use. Their technical team was very helpful and responded to any issues we had promptly.What do you dislike about Tonic.ai?Their NER model could use further development, particularly when it comes to linking identical synthesized values. Additionally, the user interface should support a wider range of file types, such as CSVs, to enhance processing capabilities.What problems is Tonic.ai solving and how is that benefiting you?This is a data company that works with large datasets, which must be anonymized for use in AI training. Their focus is on handling significant amounts of data while ensuring privacy through anonymization.

What do you like best about Tonic.ai?50+ data generators for various data types.What do you dislike about Tonic.ai?Toxic company, pretty much can do all of this with modern day LLMs.What problems is Tonic.ai solving and how is that benefiting you?We have over 2 petabytes of data and 2,000+ tables/columns, so doing this in-house is impossible. We've integrated Tonic with Gitlab to automatically trigger during a pipeline deployment, so the automation has helped our release velocity to (maybe) triple in frequency.