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OPEN TALK: The Rise of Fake Data: How to Achieve 100% Use Case Coverage with Advanced Data Synthesis


Andrew Colombi
Tonic.ai, Co-founder + CTO

Andrew is the Co-founder and CTO of Tonic, a platform empowering thousands of developers on a daily basis to create safe, synthetic versions of their data for use in software development and testing while protecting customer privacy.

At heart, Andrew is a client-focused engineer with extensive work in analytics across a full spectrum of industries giving him an in-depth understanding of the complex realities captured in data. An early employee at Palantir, he led the team of engineers that launched the company into the commercial sector. Later he began Palantir’s Foundry product, growing it into a keystone of the company’s offering.

In addition to successfully launching software products, Andrew is an accomplished pianist, composer, and cyclist, who enjoys long walks in the woods. Or so it would seem judging by how often he says, "We're not out of the woods yet."

Andrew’s commitment is not just to supply development teams with the resource-saving tools they need most, but to do so in a sustainable, scalable, and equitable manner. 

Kasey Alderete
Tonic.ai, Head of Product

Kasey is the Head of Product at Tonic.ai, a platform empowering thousands of developers on a daily basis to create safe, synthetic versions of their data for use in software development and testing while protecting data privacy. 

Kasey has found her purpose in solving business challenges with product strategy. She created business value, delivered enterprise technology and built user empathy during a robust tenure at Accenture working with Fortune 100 clients. She later honed her technical chops at MarkLogic, a NoSQL Database company, where she oversaw the inception of the flagship Data Hub product.

A proud Management Science and Engineering graduate of Stanford University, she has also served on the board of Blossom Birth and Family (a non-profit supporting expectant families), works closely with Women in Product, and enjoys traveling in South America as she speaks fluent Spanish. 

Kasey’s colleagues will tell you that she is the one to go to when you need to break through barriers stalling a project and when you simply need someone fun to hang out with. 


Quality testing is not possible without quality data. The majority of DevOps teams still burden themselves with building test datasets in-house creating a negative impact on productivity. The fragility and limitations of those custom scripts also impede QA teams in maximizing their results. With the ever-increasing complexity of today’s data ecosystems, generating useful, safe test data has become harder and riskier than ever. An effective test data solution must work across a variety of database types, while de-identifying production data in a way that ensures data privacy without diminishing data utility. A challenge? Yes. Attainable? That, too.

Test data solutions now exist that integrate directly into your data ecosystem to create test data that looks, acts, and behaves like your production data because it's made from your production data. By hydrating QA and staging with useful, safe, mimicked data, dev teams are upleveling testing, catching bugs faster, and shortening their development cycles by as much as 60%. Data mimicking sets a new standard of quality test data generation that combines the best aspects of anonymization, synthesis, and subsetting.

Discover why in-house workarounds fail to provide QA teams with the data they need and demo a first of its kind platform that:

- Increases your team’s efficiency by 50%
- Increases releases 5x per day
- Maintains consistency in your test data across tables and across databases
- Subsets your data from PB down to GB without breaking referential integrity
- Achieves mathematical guarantees of data privacy