02:15, June 28 418 0

2017-06-28 02:15:08
RAVN’s Wallqvist: We will make AI part of your life

Peter Wallqvist, the co-founder of artificial intelligence (AI) service provider RAVN Systems, confirmed yesterday that the company is looking into developing technology that could predict costs, risks and the outcomes of cases.

Wallqvist said that the prediction tool was “not productised yet”, but that RAVN was “looking into what is possible”.

“We’ve started working on it with a couple of firms and companies, it’s a natural continuation of our product set,” added Wallqvist.

This glimpse into the future was offered as Wallqvist delivered the keynote speech this morning at the ConnectLive 17 technology conference at the InterContinental hotel in Greenwich. Wallqvist was sharing the stage with senior executives from US document management specialist iManage, which acquired RAVN in May this year in a deal that he said made the new predictive-style products possible.

“This is why iManage is a really good fit,” added Wallqvist. “Before this deal a law firm had to take several steps to get to us, the lawyer had to find his own way to AI. Now with this deal, AI will come to the lawyer. We will make it part of your daily lives. We are aiming to transform how professionals work, to make them more efficient, more accurate and more client focused. That’s the long term goal.”

The short term goal, Wallqvist added, was to utilise the higher levels of investment in RAVN’s current set of solutions to allow it to enhance existing products and accelerate the development of new ones.

The development of new technology that allows lawyers and their clients to predict the outcome of cases is both a growing research field in academia and a burgeoning area commercially. In May this year a machine learning study led by Daniel Katz, a law professor at Illinois Institute of Technology in Chicago, confirmed that it is possible to use historic data to predict, with a high degree of accuracy, the future decisions of the US Supreme Court.

In the legal market there are already a growing number of tools purpose built to predict the outcomes of cases. Probably the best known litigation data mining business is Lex Machina. This was originally focused exclusively on IP litigation and is used by around half of the top 100 US IP-focused law firms along with multi-nationals such as eBay, Google, IBM, AstraZeneca and Nike. Lex Machina was bought by LexisNexis in November 2015.

Josh Becker, CEO of Lex Machina said at the time of the sale that “the only thing inhibiting our entry into other areas of the law is access to content”.

Other similar marriages of content and technology have also started shaking up the market, most notably Thomson Reuters’ October 2015 collaboration with IBM Watson.

This year’s Global Litigation Top 50 report, produced by The Lawyer in association with FTI and published next month, will look in more detail both at this trend. In particular it will reveal how the world’s leading law firms are using new technology to power their litigation practices, including by the use of AI-based tools and, increasingly, by mining their own data to predict outcomes.

RAVN’s technology reads, interprets and extracts information from documents and then converts this unstructured data into structured output in a fraction of the time it would take a human.

It was most recently in the headlines when the Serious Fraud Office (SFO) used it in its investigation of allegations of bribery at Rolls Royce, where it helped a team of investigators sift through some 30 million documents. RAVN processed 600,000 documents per day, allowing investigators to save many months of work.

Wallqvist said that the technology’s ability to help sift almost instantly through mountains of documents meant it also had applications for in-house teams. It could, he said, help legal departments move from being “an annoying little place where you go to get your contract approved to being a central department that knows what’s really going on in the company”.

He added that RAVN’s technology helped BT save £30m in costs last year.

“Once you derive structure from what was chaos you can productise analytics,” added Wallqvist.