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Synthetic data platform expands team after demand from industry

Photograph: NicoElNino/Shutterstock.com

An Edinburgh synthetic data platform has grown its headcount from two to 15 data scientists following demand from government and industry.

Smart Data Foundry’s Aizle product is being increasingly sought by clients from financial services and regulators – as it mimics real-world scenarios without the need for real data.

It means there is no need to overcome data privacy or security obstacles – allowing enterprise organisations to analyse lifelike consumer behaviours to improve their services.

SDF has released version 2.0 of its Aizle platform, which allows users to independently generate secure, high-quality synthetic data without the need for real data as input, or specialised data science expertise. 

Subscribers to the service will be able to log in and gain access to synthetic data which they can customise to their needs for a fraction of the cost of using real data, making it much more affordable for small businesses and start-ups to use.

SDF claims the Aizle platform is the ‘world’s first self-service agent-based synthetic data generation product’.

Unlike other synthetic data approaches, Aizle requires no real input data as AI agents simulate the activities of synthetic people and businesses within a customisable framework of behavioural rules and patterns. This generates data about people’s jobs, spending, and financial relationships; about businesses’ bills, cashflow, and obligations.

Created by SDF in 2023, Aizle has grown from a small research initiative employing two data scientists to a 15-strong division with enterprise clients including NatWest Group, Financial Conduct Authority (FCA), TISA and the Department for Business and Trade.

David Tracy, head of data products at Smart Data Foundry, said: “This new platform will open up the toolbox to synthetic data – until now, financial services institutions have been spending months tracking down and tidying up training data, clearing it for use with their compliance teams, and then spinning up teams of machine learning specialists to generate data on, for example, financial fraud.

“Instead, they can log in to their Aizle account, set their parameters, and the data will be ready to use within a matter of minutes or hours depending on how detailed their requirements are.

“By democratising data access, Aizle’s self-serve platform empowers users to independently generate and utilise agent-based synthetic data effortlessly, driving innovation and efficiency in their operations.

“While we are initially targeting the UK market, we can develop synthetic data for any market. We’re already building on interest internationally and intend to offer the service to financial institutions and regulators around the world.”

With the market for synthetic data generation forecast to be worth $2.1bn by 2028, according to BCC Research, SDF is already experiencing strong demand for the platform as banks, fintechs and financial regulators look for new, safer ways to innovate and build better, trusted, and valued products. 

Aizle can be used for innovation in areas previously considered too difficult or expensive to explore, where data doesn’t exist, in Gen AI/Machine Learning training and testing, and in product development and testing. 

It can also help address some of the privacy and security concerns associated with using real-world data. New data breaches and scams occur every day with recent victims including AT&T, which saw the personal data of 73 million current and former AT&T customers leaked online, and NHS Dumfries and Galloway, which had a large volume of patient and staff data stolen by cyber criminals and published on the dark web.

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