Singapore: Singapore-based startup Betterdata has raised $1.55 million in seed funding in a round, which was led by Investible, with participation from Xcel Next, Franklin Templeton, Singapore University of Technology and Design, Plug and Play, Bon Auxilium, Tenity, and Entrepreneur First. The startup uses synthetic programmatic data to create and augment datasets for data sharing that is faster and more secure than traditional anonymisation methods.
Founded in 2021 by Dr. Uzair Javaid and chief technologist Kevin Yee, Betterdata utilises generative artificial intelligence and privacy engineering to create synthetic datasets that have similar characteristics to real-world data without disclosing sensitive or private information about individuals.
Betterdata is currently in research and development partnerships with two major universities in Singapore and the United States, and its clients include Shanghai Pudong Development Bank. Betterdata plans to utilise the funding to launch its product and enhance its programmable synthetic data tech stack, as well as expand its reach beyond Singapore to more of the Asia-Pacific region in the next one to two years.
Programmatic synthetic data has several applications for developers, such as helping them protect sensitive data, comply with data protection regulations, create more data to train, increase data availability between teams, test and validate machine learning models, and address data imbalance issues by creating more records for underrepresented groups or classes.
Betterdata aims to support single-table, multi-table and time-series datasets, which are different variations of tabular datasets that address different problems, such as standalone tables, relationships between multiple tables, and data collected over time.
Investible principal Khairu Rejal said, “Betterdata solves one of the biggest issues the AI industry is facing today: lack of high-quality data that also meet privacy requirements. Through its powerful platform, Betterdata generates synthetic data that mimics real-world data without compromising quality and privacy, helping businesses meet global compliance and privacy laws at scale.”
The use of synthetic programmatic data can help developers comply with data protection regulations like GDPR and HIPAA, protect sensitive data, and improve machine learning models by creating more diverse and balanced datasets.
