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Tackling the Automation Barrier: Inside Kim Technologies' New Legal Ops Platform

One of many companies offering ways to automate legal workflow tasks, Kim Technologies is finding footholds in some of the largest legal departments across the globe. Its technology is already being deployed at Vodafone to streamline its contract management, and it's also being tested in artificial intelligence pilot projects at Cisco.

Bringing automation and AI-powered workflows in-house, however, can be challenging for many legal departments, requiring significant resources, time and patience. But Kim Technologies—most widely known through its association with investor and partner Riverview Law—is hoping to address those pain points with the launch of its Intelligent Legal Operations Platform.

Legaltech News spoke with Kim Technologies CEO Robert Farina to discuss how this new platform hopes to make bringing automation in-house less burdensome, and how it stands up against the other big configurable automation and AI contender in the corporate legal tech market.

LTN: What is Kim Technologies' new Intelligence Legal Operations Platform?

Farina: The Intelligent Legal Operations Platform is a complete, configurable workflow automation, case management, document management, end-to-end system. In other words, it can be applied to many different tasks within legal ops. For example, contract and in-life management, employment work, compliance processes, etc.

Say that I need to generate a contract or an NDA or some other document from my legal sources and get it to a prospect. The Intelligent Legal Operations Platform can set this up and it can be completely self-service. So it can generate a document and send it back, and a lawyer does not does to get involved.

The platform can also be used as a gateway to the legal department to request help from a legal staff member, so someone in the business can submit a request for help, and it could then be routed to the right individuals within the legal staff.

How does this platform ease implementation?

All you need to access our system is a web browser and internet, no one is writing any code to configure our system.

We are able to train our customers [on how to configure the platform] so if they wish to be self-sufficient they can be, but they don't have to be as we have our own services to help.

The key point here is that the coding has already been done. So if you are an administrator of Kim you have access to all the configuration tools, the things that establish a workflow, that read a document and define what information you want to get out of those documents, all those tools are available.

What role does AI play?

There are pieces of the platform that use AI and there are pieces of it that are fairly straight business automation tools.

Behind the scenes we primarily use a form of AI called neural networks that allow the systems to be highly configurable so that the platform can be easily flexed and configured to do a number of different things without the need for IT resources.

We can also use that AI capabilities to inform automated routing. And it's not just a matter of routing this document to a particular person. We look at it form an optimization point of view, so who has the right skills, who has the right experience, who has the workload, and then route that work all that work accordingly.

On the cognition side, one of the ways we've been able to implement [data review] very quickly and get a high percentage [of accuracy] without going through the extensive training process of machine learning is using something called a single model intelligence approach, which has patents pending.

This allows a company to put any of their best practices, templates, or predetermined standards into the system to take a third-party document, for example, assess and compare it against [this single point of data], and come up with a high degree of evaluation.

So how is this different from Kim's virtual assistant?

Virtual assistants are pre-configured version of Kim that were designed by our partner, Riverview Law, to address specific common use cases, for example, instruction and triage, and they come with a set of pre-configured dashboards that track data.

How does this platform compare to IBM's Watson Discovery Service?

That particular services appears to me, and I do not know it well, to be limited to finding information and not necessarily to acting on it in the way we do in terms of the routing, workflows and document assessment and those things.

A lot of these machine learning platforms are taking what we are calling an outside-in approach, where they ingest these huge amounts of data from external resources to identify patterns and correlations that might be important. Kim, on the other hand, works from the inside-out.

We're going to your company and saying, OK, what is important? You give us your documents, your workflows, best practices, standards or templates and we are going to use that to configure how the AI will be used.

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Rhys Dipshan

Rhys Dipshan is a journalist who covers in-house tech issues from early disruption to ghosts in the machine for Legal Tech News, The National Law...

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