Snowflake Startup Spotlight: VEIL.AI

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, meet CEO Tuomo Pentikäinen and CTO Timo Miettinen, the founders of VEIL.AI and see how they are aiming to revolutionize AI-driven healthcare by developing privacy-enhancing technologies with a specialty in the anonymization of sensitive data.

Who are you and what inspires you? 

We are a diverse team of experienced data scientists, computer scientists and data engineers complemented with seasoned global business leaders. We are passionate about changing the future of healthcare by enabling better health research with next-generation data anonymization.

What problem does VEIL.AI aim to solve? How did you identify that issue?

VEIL.AI is a deeptech company that offers scalable solutions to anonymize or synthesize sensitive data while preserving exceptional data quality and utility.

Our founding team comes from the deep end of European life sciences: the Institute for Molecular Medicine Finland. We were managing massive amounts of data, and the need for high-quality, rapid-access data was booming. However, the data was nearly always the sensitive healthcare information of private individuals.

We analyzed existing data anonymization and synthesization tools and realized that they produced inferior data quality, were difficult and labor intensive to use, and required far too many computational resources. We wanted to solve this issue, because we believe that data can solve the biggest problems of mankind. But for that to happen, data must flow in a way that inherently respects privacy.

How does your technology accomplish that?

VEIL.AI next-generation anonymization transforms health data into high-quality, individual-level anonymized data sets that are compliant with privacy regulations and guidelines (GDPR, EHDS, HIPAA, NIST, CMIA, etc). The VEIL.AI Anonymization Engine, a Snowflake Native App, is optimizing and automating anonymization to produce the best possible quality, row-level anonymous data with a high level of data privacy — and automatic privacy and quality reports for evidence. Leading organizations, including global pharmaceutical companies, top-tier research institutions and health data permit authorities, trust VEIL.AI for their most sensitive data needs without compromising data privacy and utility. 

VEIL.AI gives healthcare organizations tools for secure and efficient secondary use of data for research, development, management and innovation. We’re unlocking new use cases such as safe AI training, accelerating clinical trials, generating real-world evidence and fostering cross-border data collaboration.

What’s the coolest thing you’re doing with data? 

We were able to provide anonymized real-world data to model a synthetic control arm in a clinical trial. This peer-reviewed published pilot was extremely cool, because it is about as difficult a task as you can find. And especially because synthetic control arms can be life-changing and life-saving solutions, such as in single-arm studies where traditional control setting has been typically impossible or unethical. This can be the case, for example, in pediatric diseases, rare diseases or diseases with poor prognosis.

How has the Snowflake Native App Framework enabled you to push the envelope in your line of business? 

We are dealing with sensitive data and we want to bring our data anonymization tool to where the data is. Accessing the native app directly in Snowflake allows our customers to incorporate the VEIL.AI Anonymization Engine as part of their data processes. Snowflake also streamlines vendoring processes: clients using Snowflake have already made the security test and screenings, and they are familiar with the UI. For example, an organization could use VEIL.AI’s Snowflake Native App to anonymize part of their sensitive data and leverage Snowflake Marketplace to monetize their data securely, or to share access to anonymized data with collaboration partners.

How has the Snowflake Native App Framework shaped your startup's growth and development strategy?

We expect the Snowflake Native App Framework to shorten our sales cycle significantly, as we are now building an app within the familiar Snowflake UI, and no specific security tests or technical acceptances are needed.

Global GTM exposure through this framework is the game-changer for us. We want to offer an easy to use (and easy access) solution to a highly complex problem. Selling a new platform, new UI and new technology would just be too complicated. For us, the Snowflake Native App is an obvious choice, as it makes GTM easy. We can deploy our software in the Snowflake workflow and platform that our customers are already using and are already familiar with, and which has already passed all their security and acceptance requirements. 

What's the most valuable piece of advice you got about how to run a startup? 

 A former very successful software executive advised us to try to keep the variables down to one. If you are selling a new product to a new market, there is probably one variable too many. If you are selling a new tool, it is much better to get it into an existing toolbox than to try to sell a new toolbox at the same time.

For us, Snowflake is the toolbox, and we can keep only one new variable: our Snowflake Native App.

What's a lesson you learned the hard way? What would you do differently?

For a startup it is extremely hard to get into the vendor list of a global blue chip. The sales cycle can easily be one or two years, if not more. It does not scale up. We should have chosen the Snowflake Native App strategy earlier, because it removes the majority of the decision-making barriers. Moreover, the global reach and brand benefit of a strong partner like Snowflake is very important in sales. 

AI is on everyone's mind. How has it impacted your startup? 

We see the potential of AI on three levels. First, we use AI very extensively to facilitate the complex problem of optimizing the anonymization process in terms of data utility and privacy safeguards. Secondly, we deliver our product as an integrated part of leading AI platforms like Snowflake. Thirdly, we invest a lot in AI agents to optimize the use of human resources and to minimize unnecessary bottlenecks.

AI needs a lot of data. A big portion of the easily available nonsensitive data is already in use. The next AI waves will require the opening up of sensitive data sources. This cannot be done without privacy-enhancing solutions like anonymization or synthetization.

What’s on the horizon for you? What role will your company play in the industry’s future?

By the end of 2033, we would like to see VEIL.Al as a global leader and a trusted partner in data anonymization and synthetization technologies for leveraging sensitive data to its full potential.

Learn more about VEIL.AI’s solutions to help organizations transform sensitive health data into high-quality, privacy-compliant assets at https://veil.ai, try the VEIL.AI Anonymization Engine 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, check out the Powered by Snowflake Startup Program for info on how Snowflake can support your goals.