UiPath Inc. continues down the path to automate the mundane in the workplace.

The company’s Business Automation Platform is making strides to automate processes by using process mining and task mining to enable its robotic process automation to learn quickly and on the fly. 

“Before we automate something, we often like to do what we call communications mining, which is really understanding what all of these messages are about that might be hitting a part of the business,” said Edward Challis (pictured, left), general manager at Re:infer, a UiPath company.  

For example, for a large financial business, there may be a sudden uptick in messages from clients. What communication mining does is analyze the high-volume query categories to manage the requests in a more timely manner.

Challis and Ted Kummert (pictured, right), executive vice president of product and engineering at UiPath, spoke with theCUBE industry analysts Dave Vellante and David Nicholson at UiPath Forward, during an exclusive broadcast on theCUBE, SiliconANGLE Media’s livestreaming studio. They discussed how the Re:infer acquisition is bringing enhancements to UiPath’s Business Automation Platform. (* Disclosure below.)

UiPath targets business efficiency

UiPath’s platform began with robotic process automation, applying automation to the issue of integration of applications. Then in 2019, the company announced its end-to-end hyperautomation platform. By leveraging process discovery tools and crowdsourcing from employees, it can more accurately determine what to automate and increase the efficacy of its platform. 

“What we’ve seen happen with our customers is that their use of [the platform] goes from being very heavy in automating the repetitive and routine to being more balanced, to now where they’re implementing new brought business process, new capability for their organization,” Kummert stated.

This advance to automating new processes previously unthought of brings some very interesting implications for businesses in future, with employees adapting to a more productive work cycle alongside software-defined robots. 

“Early on, [customers] talk a lot about hours saved, and that’s great. But then what about the business outcomes it’s enabling? The transformations in their business?” Kummert said.

UiPath leverages Re:infer technology

UiPath’s recent acquisition of Re:infer has brought several improvements in language processing to the UiPath platform. These include identifying messages that commonly begin with similar words or alphanumeric strings and taking and interpreting those messages. This drives the process of automating what have traditionally been human channels. 

When it comes to getting a machine learning model into production, one of the principle drivers is training.

“What we use is a technique called active learning, which is effectively where the AI and ML model queries the user to say, ‘Teach me about this data point; teach me about this sentence,’” Challis said.

This user query model is effective because it allows humans to decide how the model should encode an interpretation of an event. 

“It’s important that the client, our client, the user of Re:infer, can encode what their notions of good and bad are,” Challis added.

Here’s the complete video interview, part of SiliconANGLE’s and theCUBE’s coverage of the UiPath Forward event:

(* Disclosure: TheCUBE is a paid media partner for the UiPath Forward event. Neither UiPath Inc., the sponsor for theCUBE’s event coverage, nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo: SiliconANGLE