Kortical Pledges To Turn Businesses’ ML Failures Into Success

The promise of machine learning (ML) and artificial intelligence (AI) is that it will help your business find the secret sauce in its data, catapulting you ahead of the competition. Far too often, however, these technologies fail to deliver. Research from Gartner suggests 85% of big data projects fall short – and by 2022 it expects this to have improved by just five percentage points.

Now, however, a British technology start-up claims to have developed a suite of tools that can help businesses dramatically tip the odds of data projects succeeding in their favour. Kortical says its platform will save businesses the time and effort of developing their own AI and ML tools, which may or may not deliver; instead, businesses can use Kortical’s own solutions to parse their data for the business insight they require.

How can potential clients be confident Kortical’s platform will work any better than their own solutions? Well, Kortical CEO and founder Andy Gray points to the company’s track record working with clients ranging from the global accountancy giant Deloitte to the UK’s National Health Service. Its tools have been deployed to help businesses reduce wastage, drive productivity and introduce automation.

“At the moment, businesses are still in the early days of the machine learning gold rush, where you can crest a hill and stumble upon a nugget,” Gray explains. “Better ML accelerators are like better metal detectors that help you find those nuggets faster.” In this analogy, Kortical is the provider of your metal detector. The company says clients have enjoyed positive return on investment outcomes in 92% of deployments so far.

Gray is particularly proud of Kortical’s record in challenging Google’s Vertex AI technology. The companies went head to head two years ago at a “Datathon” run by the investment company Schroders, with platforms asked to crunch through public dataset from Kaggle and a real-life client. Kortical delivered a performance that was 2.47% better across all datasets and 10.75% better on the real-life client – an improvement that would have delivered £500,000 of additional savings, it claims. Kortical also delivered its results seven times’ more quickly.

The company’s value proposition is built on the belief that a broad range of businesses and other organisations are excited by what AI and ML technologies have to offer, but nervous about how to take advantage. Skills are in short supply, technology can be expensive, and there are no guarantees of success.

Even the largest companies are struggling with these challenges, Kortical points out. Clients such as Deloitte see the potential to drive efficiency and productivity but have chosen to use its platforms to crunch the data. At the NHS, Kortical helped deliver a 54% saving on blood supply chain wastage for the taxpayers who ultimately fund the service.

Gray believes that the ML sector is now beginning to come of age. “Initially it was really only the big players that were the early adopters – they had the luxury to experiment with new technology and those experiments have turned into significant business,” he says. “Increasingly we’re now seeing smaller businesses that recognise the strategic advantage and huge potential of ML to really distance themselves from their competitors.”

As acceptance grows, however, Kortical believes more businesses will choose to partner with specialists like it, rather than trying to develop their own in-house competencies. It points to Gartner research estimating that by 2022, 75% of all new end-user solutions using AI and ML techniques will be built using commercial solutions rather than open source.

The company’s tools are essentially aimed at any organisation that has a data set and a business problem it wants to solve. They work with tabular and time series data, as well as natural language processing, with popular use cases so far including back office automation, demand prediction and hyper-personalized marketing.

“The conversation has shifted from do I need a machine learning accelerator platform, to which platform should I use?,” Gray says. And with more companies now focusing on the growth agenda as the global economy begins to recover from the Covid-19 pandemic, Kortical believes adoption rates will accelerate.

Gray adds: “Over the past 12 months, businesses have focused on continuity and their remote work set ups, but this year we’re seeing signs of growth getting back to 300% year-on-year and will be looking to raise an investment round by the end of the year.”

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