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Kaybus and the Race to Automate Knowledge

By Jim Lundy

Knowledge management is one of the most hotly-debated topics of the modern era and until now, most efforts have used a set of collaboration, learning, and content management band-aids to try to deliver knowledge.

Kaybus, a San Francisco-based startup, is aiming to change all of that. This blog post talks about the shift to a new category we are referring to as knowledge automation.

Making Knowledge Automatic

When people ask me about learning and knowledge, one of the things that I get asked is, “Why is it so hard to share knowledge?”

The answer often has to do with the tools that are being used, and today, that is often the reason that corporate learning initiatives are liked by learning and development (L&D) personnel, but hated by the average user.

The complaint is this: “My people are still missing the knowledge they need to do their job.” Jump ahead to today and we have identified a set of technologies that combine machine learning with content and analytics—forming the ability to identify knowledge gaps and then correct them with curated content (a.k.a. knowledge campaign). This is knowledge automation and this is what Kaybus is delivering.

Kaybus and Knowledge Automation

Kaybus has developed a platform that can fix the problem so many companies face—getting the right information to the right people in an automated fashion. Kaybus co-founder and CEO Seenu Banda had a vision and his team has been working hard over the last two and a half years to make the dream of knowledge automation a reality.

We liked the fact that the Kaybus platform is content agnostic; it can search for and find videos, something that you normally need a dedicated video content management platform to do.  To us, that demonstrates good design, since nearly all learning and content management platforms have a tough time with managing video. As more and more learning content becomes video-enabled, we expect the demand for knowledge automation will soar.

Predictive Leads and Now, Predictive Knowledge

At Aragon, we made the call on the rise of predictive business applications in early 2014. We got many calls last year about a related predictive category: predictive lead scoring for sales.

In 2014, that category was new, but it exploded. Firms like Box used predictive lead scoring to drive revenues and get to an IPO. We think the same holds true for the knowledge automation category in 2015. In fact, our new Technology Arc for the Digital Workplace includes an entry for knowledge automation on the emerging arc.

Knowledge Automation: More Than Hype

The race is on to make business applications that help people get to better outcomes. While learning management systems (LMS) track, report, and launch training courses, knowledge automation (KA) platforms will learn what the user needs and deliver it to them. There is a tie with this to predictive content, but knowledge automation does much more than just finding content you might need—it also helps to measure the needs of teams and departments and suggest a knowledge campaign.

We have spent time with some of Kaybus’ early customers and they are leveraging the Kaybus KA capabilities and it is making a difference in performance. Knowledge automation is here and leading sales, service, and support organizations are jumping in.

Editor’s Note: Jim Lundy is the founder and CEO of Aragon Research. He oversaw the Content, Collaboration, and Knowledge Management practices at Gartner for over 12 years.

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