Empowering Data Teams with Native Data Privacy Solutions

Welcome to Snowflake’s Startup Spotlight, where we ask startup founders about the problems they’re solving, the apps they’re building, and the lessons they’ve learned during their startup journey. In this edition, hear from DataMynd.ai Founder and CEO Chuck Frisbie about how synthetic data is the answer to balancing the need for data privacy with the need for data access, and some of the unexpected benefits of their Snowflake Native App.

How would you explain DataMynd in one sentence?

Datamynd builds data privacy solutions for Snowflake Marketplace and our first Snowflake Native App, the Synthetic Data Generator, allows data teams to generate highly accurate synthetic data without sacrificing security or privacy.

What inspires you as a founder?

Delighting customers with thoughtful, well-matched solutions inspires us. A great solution makes someone’s day because it’s exactly what they need for a specific job.  Great solutions empower teams, save time and headaches, and are easy to work with.  Nothing is better than a customer thanking you for giving them a great solution.

Countless times we’ve thought, “Wouldn’t it be great if there was a product for X?” Well, we’re taking those products and making them portable, more intelligent and consumable in an enterprise data setting. Our solutions are easy to use, leverage native platform capabilities, and synergize with each other.

What problem does DataMynd aim to solve? How did you identify that issue?

Our debut Snowflake Native App, Synthetic Data Generator, offers a simple solution for a complex problem: unlocking the value of sensitive data is a pain! Whether sharing data for analytics, training ML models, or creating dev or test data, data privacy can get in the way of innovation. Rather than scrubbing or redacting sensitive fields — or worse, creating rules to generate “realistic” data from the ground up —you simply point our app at your production schema, train one of the included models, and generate as much synthetic data as you like. It’s basically an “easy button” for synthetic data.

Our Snowflake Native App uses machine learning to profile a real data schema and generate similar, high-quality synthetic data from it. Our synthetic data contains similar trends and correlations to the real data, making it more useful than traditional test data. You can even train ML models on our synthetic data, or use it for data sharing purposes. 

While the app itself is cool, we’re seeing some really interesting benefits including reducing regression bugs, building better dev and demo schemas, rebalancing biased datasets, and even scale testing.

Why did you choose to build your app on Snowflake? 

The Snowflake Native App Framework removes many of the barriers between us and our app consumers. Since our apps focus on supporting ML and data privacy workloads, being able to deploy safely to a consumer account is huge for our customers. It really cuts down on the vetting process, which benefits everyone.

The other aspect of the Snowflake Native App Framework is development speed and minimizing developmental overhead. As developers, we want to focus on the core workflow, not on the infrastructure and plumbing side of things. With Snowflake, each component feels modular but supports great integration with the rest of the framework.  All of this means we can focus on the core workflow and produce a lot in a short amount of time.

As a Snowflake Native App builder, we also get exposure to thousands of Snowflake customers and potential selling opportunities. We already have a lot on our plates as a small dev shop, so having an additional avenue for inbound leads and referrals has made a huge impact on acquiring early customers and feedback on our apps.

What role does AI play at DataMynd? 

At DataMynd, we use AI as a core part of our app — we train neural networks in order to generate high-quality, accurate synthetic data — and we aspire to create safe synthetic data that can power AI use cases.  

Data access will be a key part of the accelerating AI tech scene, but it’s juxtaposed against the rise in data breaches and growing data privacy concerns. Synthetic data is one technique that companies can use to balance these two forces, and we’re very excited to be involved on that front.

The rapidly changing AI landscape is on everyone’s mind. As a founder and innovator, what’s your perspective on how AI is impacting the business world? 

I’m a bit more optimistic than some about the rise and risks of AI. The next few years will certainly be a roller coaster of a ride. We may have some scary moments, but remember, our tools for solving these challenges are the same ones creating them.

I don’t think AI will replace the majority of jobs in the data space. I think we’ll get a boost in general efficiency for many existing roles, but we will also see an appetite for increasingly intelligent outcomes, and there will be a huge opportunity for new roles for those who are able to reinvent themselves.

I also think we will see a ton of tactical AI-driven apps, rather than a monolithic, general purpose AI-for-everything. That is an exciting premise for someone building AI apps!

Learn more about DataMynd and the value of synthetic data at datamynd.ai, try their app on Snowflake Marketplace or read the company’s post on the Snowflake Builder Blog on Medium for technical details. If you’re a startup building on Snowflake, don’t forget to register for the 2025 Snowflake Startup Challenge and check out the Powered by Snowflake Startup Program!