Statice is an automatic data anonymization software that generates entirely anonymous synthetic data. This synthetic data preserves the structure and utility present in the original data. Unlike traditional anonymization technologies and products, Statice enables highly complex secondary data use cases such as building performant machine learning models on anonymous data. It ensures that no personal information is ever exposed by providing privacy-preserving synthetic data which allows companies to run meaningful data analysis on a new synthetic dataset without ever touching original data.
With data privacy becoming more and more relevant under regulations such as the GDPR, Statice enables the easy processing of highly sensitive and critical customer data.
The Mission That Drives Statice Successful
The company’s mission is to allow data-driven collaboration between organizations, to unlock undiscovered insights, solve business problems, and accelerate product development. With personal data becoming scarcer in times of GDPR, Statice is an enabling power for data-driven innovation. Statice unlocks sensitive customer data for companies while protecting consumers by securely anonymizing this data.
In today’s growing customer-centric economy, innovation begins with understanding people. Companies partly do this by measuring, tracking, and storing personal data on individuals in order to quantify personal preferences and use this knowledge to tailor experiences and products towards each customer individually. Personal data is the core source of modern services and products and serves as the most important resource for the majority of modern technological advances and discoveries. This does not only hold viable for scientific settings but also for corporate R&D.
At Statice, the company believes in two major trends. First, data privacy is becoming an increasingly important asset for enterprises in order to provide trust. Second, innovation will build on collaboration across players and data as the main resource.
As anonymous data is exempt from data privacy regulations, the company decided to build Statice as an enabling power of both trends: protecting individuals on one side and empowering data-driven innovation and collaboration on the other side.
The Passionate Leaders
Statice was Co-founded by Sebastian Weyer, Co-founder and CEO; Mikhail Dyakov, Co-founder and CTO; and Omar Ali Fdal, Co-founder and CDO. Their backgrounds range from business, software development to data science. The founders collectively cover all areas necessary to build the company and to provide its customers with the best possible solution to anonymize and protect their customers’ data.
“Our backgrounds made it possible for us to understand the problem we are solving from a business as well as technological perspective and to tailor our solution in a way that it solves the problem from both perspectives”, said Sebastian.
Statice launched its product at TechCrunch Startup Battlefield in Paris earlier this year and are now serving customers in the healthcare, automotive, pharma, insurance and financial sector. The feedback around the data quality Static provides has been tremendous. Companies are realizing that leveraging otherwise sensitive data is so much easier with Statice and takes away a lot of effort when from example sharing data with partners for building product collaboratively.
Data Fuels Technological Innovation
Sebastian sees Statice as an enabler. Data, and especially customer data, is the most important resource for building machine learning and artificial intelligence applications. Data is a necessary resource that can unlock consumer insights, drive forward research, and fuel better products.
“The use of critical data becomes more and more difficult due to the increasing importance of data privacy. This all raises one big question: How can we enable data-driven collaboration while protecting consumers?” he said.
The answer is data anonymization – because truly anonymous data is not subject to data privacy regulations. Statice makes data anonymization easy. Unlike traditional anonymization methodologies, the company also preserves the structure and statistical properties of given original data. By leveraging the recent advances in machine learning and state-of-the-art privacy techniques, Statice enables companies to work on privacy-preserving and highly granular datasets with no risk of identifying a single individual. This enables the training of complex algorithms without the use of sensitive data in the first place.
Unmatched Approach to Building Data Privacy
Truly anonymizing data is difficult. Anonymizing data in a privacy-preserving manner takes time, resources, and significant domain expertise. Traditional anonymization technologies usually have two problems. Either they are not sufficient and do not protect data properly enough, or they change data to an extent where it is barely usable for a variety of use cases
So, even if the generation of truly anonymous data has been successful, this often equals a significant loss in data utility, thus rendering an anonymous dataset useless. “This is why we built Statice – to combine the best of both worlds. Statice is the first anonymization software that enables the generation of guaranteed privacy-preserving data while minimizing the loss in data utility, added Sebastian.
Sebastian feels the biggest challenge Statice faced in the process of building the company was to actually make its vision work. “As mentioned before, truly anonymizing data alone is not difficult. Anonymizing data while preserving its utility is even more difficult. It took us a lot of work and research to develop the product we have today. So far, the feedback has been amazing and using synthetic data for various use cases instead of sensitive original data has shown to be an amazing way for our customers to work with data in a privacy-preserving manner”.
The company’s current challenge is about educating the market about its product and to show how anonymizing data does not always have to be associated with losing data utility. Statice wants to show that building customer-facing machine learning applications does not require massive amounts of sensitive data but can happen on anonymous synthetic data through its product.
Statice’s vision is to be the central privacy-preserving data hub for data-driven collaboration across enterprises. The company believes that collaboration is a major driver of innovation. With data being an essential resource for modern innovation and data privacy a major barrier for data-driven innovation, starting with providing a software to protect data privacy was the logical first step for the company.
“Next, we want to enable companies to get together and collaborate on their synthetic data. We want to achieve this by providing a data marketplace in the form of secure end-to-end platform for companies to share and combine their synthetic data with selected partners. This marketplace is future fuel for the AI economy” commented Sebastian on the future plans.