Alan Hambrook, Aleri's co-founder and chief executive, is a long-time specialist in financial reporting software for the banking sector. When one of his biggest financial services clients suddenly acquired one of its main competitors, he knew he faced a mammoth task: to build a system capable of aggregating 50 million trading values and producing a variety of reports from two million rows of results data – all by 6 am every morning.

To help him with the task, Hambrook approached a friend at the European Space Agency. How, he asked, could he build a system capable of performing billions of calculations in a matter of seconds. The secret, he discovered, lay in the database architecture.

Instead of using a standard relational database, the ESA had adopted a database modelled on an entirely different branch of mathematics: vectors. Adopting a vector database can mean performance improvements of a factor of up to 800 over a standard relational database, says Hambrook.

Aleri used this technology as the foundation for its 'near-real-time analytic infrastructure' and tuned it for more mainstream commercial use. Today, its technology takes data from operational sources and message queues, either continuously or at pre-set intervals, and feeds it into the engine. Because of the sheer speed with which its software can perform mathematical calculations, it is ideal for large-scale data analysis, says Hambrook.

Users back up these claims of performance improvements. Flagship customer Allied Irish Bank reports that its daily trading analysis, which used to take around 12 hours to run, takes a mere 12 minutes using Aleri.

Such results make Aleri's technology a compelling proposition to major corporations that need to make sense of vast – and soaring – volumes of data. VC firms, recognising this, have invested $10 million (€11.1m) this year to finance the company's growth.

Verdict: Aleri's business proposition will undoubtedly appeal to big organisations that need to react quickly to customer information. But the company still has to prove that its analytical technology has hit a level of maturity that makes it relatively easy to use and maintain.