About a-team Marketing Services
The knowledge platform for the financial technology industry
The knowledge platform for the financial technology industry

A-Team Insight Blogs

Shape Releases AI-based Data Monitoring Solution for Data Management and Data Science

Subscribe to our newsletter

Shape, a Brussels-based start-up, has released a data monitoring solution for data management and data science that is built on machine learning and artificial intelligence (AI) technologies and designed to ensure data is trusted and fit for purpose.

When used as a data management tool, Shape.AI allows data science and analytics teams to define their data quality expectations in a self-service way and monitor the expectations. When issues arise, teams are alerted and can identify the root-cause of problems and decide on resolution.

From a data science perspective, Shape.AI allows data scientists to define and monitor data quality expectations as they build data models using both internal and vendor data sources and move them into production.

Maarten Masschelein, co-founder and CEO at Shape, says: “As firms rely more on data every day, it is key that they can trust the data. There are a variety of components of trust, one is the need for data to be fit for purpose as data products are developed and put into production. We focus on DataOps around data products and operations. To do this, we are evolving a data quality monitoring platform that goes beyond legacy data quality tools built around ETL and data warehouses.”

The platform uses machine learning and AI to check production data consistently against expectations and identify any anomalies that should be investigated. It is cloud native and is implemented to allow self-service, rules-based testing based on a library of tests developed by the company in collaboration with industry experts.

The company is working with a large asset manager in the Netherlands, which helped to co-design the software, to use a rules-based approach to make sure all statics funds data is of high quality before it is exported to customers and internal and external reports. Further work will dive into other datasets to check data quality, bring any anomalies to attention immediately, and hopefully before they break anything, and build trust in data.

As the company heads towards its first birthday on April 27, 2019 with a staff of five and the benefit of a €500,000 government grant received in February, Masschelein notes good progress with the asset management firm up and running with Shape.AI and proofs of concept about to take place in the US, Germany and London. In other sectors, the company is working with HBO and Expedia.

Subscribe to our newsletter

Related content

WEBINAR

Recorded Webinar: Are you making the most of the business-critical structured data stored in your mainframes?

Fewer than 30% of companies think that they can fully tap into their mainframe data even though complete, accurate and real-time data is key to business decision-making, compliance, modernisation and innovation. For many in financial markets, integrating data across the enterprise and making it available and actionable to everyone who needs it is extremely difficult....

BLOG

Implementing and Understanding Modern Data Architectures: Webinar Preview

The evolution of data use by financial institutions has been accompanied by ever-changing challenges to its management. With technologies such as artificial intelligence enabling firms to prise greater value from their data and to subject it to greater utilisation, a new set of data management practices have emerged. These modern data architectures regard data as...

EVENT

Data Management Summit London

Now in its 16th year, the Data Management Summit (DMS) in London brings together the European capital markets enterprise data management community, to explore how data strategy is evolving to drive business outcomes and speed to market in changing times.

GUIDE

AI in Capital Markets: Practical Insight for a Transforming Industry – Free Handbook

AI is no longer on the horizon – it’s embedded in the infrastructure of modern capital markets. But separating real impact from inflated promises requires a grounded, practical understanding. The AI in Capital Markets Handbook 2025 provides exactly that. Designed for data-driven professionals across the trade life-cycle, compliance, infrastructure, and strategy, this handbook goes beyond...