The algorithm – a set of instructions that perform a particular mathematical operation – is the workhorse of computer-aided analysis. For decades, algorithms have been applied to complex industrial problems as diverse as chip design and delivery route planning.

But according to Daniel Hulme, CEO of UK-based start-up Satalia, businesses are well behind the times when it comes to algorithmic analysis. He says the pace is set by academia, but adds that most cutting-edge algorithms developed by computer scientists never make the jump into industry.

“It’s very difficult for academics to commercialise their algorithms because they’ve got such short shelf lives – six months after they’re published someone will write a better one,” he explains. “And businesses don’t want to go through the processes of negotiating with academia for the same reason.”

It is this gap that Hulme hopes to bridge with Satalia. Spun out from University College London in 2008 and based largely on Hulme’s own academic work, the company aims to become “the iTunes for algorithms” – an online marketplace for the very latest algorithms.

Today, most algorithms used in industry are embedded into specialist applications, explains Hulme. For example, logistics companies will use dedicated software to plan out their delivery routes (a surprisingly complex mathematical operation) and will most likely be unaware that the calculation is being done algorithmically.

“The algorithm that’s built into that software is likely to be ten or fifteen years behind the state of academia,” says Hulme. A number of very powerful classes of algorithm have been developed in the last decade, he says, that could improve everything from drug discovery to financial investment strategies.

The technology Satalia has developed is a machine-learning tool that analyses problems (once they have been defined in a standardised manner) and identifies which kind of algorithm would be most suitable for solving them.  

Hulme hopes that one day this will allow businesses to upload their complex analytical problems to Satalia’s online “Solving Engine”, and receive automatic access to the latest and most powerful algorithms. “Our goal is to be the optimisation engine behind everything,” he says.

The company is not quite there yet. For one thing, few companies have defined their problems in the required format, and to do so requires some consultative work from Satalia.

It has made in some roads into industry, however. Satalia’s initial focus was on semiconductor companies, which already use algorithmic analysis to design new chips and in many cases have adopted standardised problem definitions. But while it has had some success here, Hulme says he has found the sector “very bureaucratic and mature, and difficult to penetrate”.

As a result, the company is now broadening its focus to include other sectors, including pharmaceuticals and logistics.

An obvious target for London-based Satalia is the financial services industry. Investment banks commonly apply sophisticated algorithms to problems such as equity portfolio optimisation, but Hulme believes even they are behind the times.

“The quants [quantative investment analysts] are very clever, but they are not using these new families of algorithm that they really should be using,” he says. “If they were able to convert their problems to the format that our systems understand, they’d get access to a portfolio of a thousand algorithms from many, many different areas of computer science.”

Again, though, Hulme is encountering some hurdles. “People in the finance sector have said to me, ‘You’re commoditising algorithms’,” he says. “In some cases we are, but if a bank wants to pay a premium for exclusive use of a particular algorithm, we’ll give it to them.”