Startups Betterdata uses synthetic data to keep real data safe

Betterdata uses synthetic data to keep real data safe


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Better data, a Singapore-based startup that uses programmable synthetic data to keep real data safe, announced today that it has raised $1.55 million. The seed round, which it said was oversubscribed, was led by Investible with participation from Franklin Templeton, Xcel Next, Singapore University of Technology and Design, Bon Auxilium, Tenity, Plug and Play and Entrepreneur First.

The startup was founded in 2021 by Dr. Uzair Javaid, the CEO, and chief technologist Kevin Yee, with the goal of making data sharing faster and more secure as data protection regulations expand around the world. The company currently has research and development partnerships with two major universities in Singapore and the United States (it cannot disclose who they are), and its clients include the Shanghai Pudong Development Bank.

Betterdata says it differs from traditional data sharing methods that use data anonymization to destroy data because it uses generative AI and privacy engineering instead.

Yee explained to that programmatic synthetic data uses generative models, such as deep learning models, including generative hostile models used in deepfakes, transformers used in ChatGPT, and diffusion models used in stable diffusion, to create new datasets and expand.

These synthetic data sets have similar characteristics and structure to real world data without disclosing sensitive or private information about individuals.

“The idea is to create a fictitious version of a real dataset that can be safely used for a variety of purposes, including protecting confidential data, reducing bias and improving machine learning models,” he said.

Programmatic synthetic data helps developers in many ways. A few examples include helping them protect sensitive data, comply with data protection regulations such as GDPR and HIPAA, increase data availability between teams, create more data to train, test, and validate machine learning models, and Address data imbalance issues by creating more records for underrepresented groups or classes.

Betterdata’s funding will be used in product launch and to enhance its programmable synthetic data technology stack, including support for single-table, multi-table, and time-series datasets. These are different variations of tabular datasets, and Yee explains that the main differences are their structures and the problems they were created for.

For example, single-table datasets focus on standalone tables, while multi-table datasets are for considering relationships between multiple tables, and time-series datasets are about data collected over time.

Betterdata also plans to hire more people, including sales and marketing associates, and expand beyond Singapore into more of the Asia-Pacific region over the next one to two years.

In a statement on the investment from Investible, director Khairu Rejal said: “Betterdata solves one of the biggest problems facing the AI ​​industry today: lack of high-quality data that also meets privacy requirements. Through its powerful platform, Betterdata generates synthetic data that mimics real-world data without compromising quality and privacy, enabling businesses to comply with global compliance and privacy laws at scale.”

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