A team of former Microsoft execs and engineers have launched Highspot, a startup with a new cloud knowledge management service that helps organizations capture, share, and cultivate their most valuable working knowledge via machine learning.
Highspot’s chief scientist, Paul Viola, ran the core data science team for Microsoft’s Bing search engine and helped it to pull even with Google in many measurements of search relevance during his tenure. Viola described himself to eWEEK as a "machine learning geek."
In a blog post about the company’s launch, Highspot's CEO Robert Wahbe, who was corporate vice president of product management for the Server and Tools Division at Microsoft, said the inspiration for Highspot came from its founders' collective frustration that their previous organizations had the potential to be much more effective if they "only knew what they knew."
"We spent a ton of time and money producing content, and what came clear to me was that people are not able to find the content they are looking for when they need it," Wahbe told eWEEK. Wahbe cited a Forrester study that says there is a knowledge gap where the failure rate for not finding the information users are looking for is 56 percent, while the process of looking for the information wastes up to 12 percent of users' time.
According to Wahbe, "The information existed to make the organizations smarter, but it simply wasn't available to the people who needed it, when they needed it. Some of this vital working knowledge was formal, such as documents and presentations about a new product launch, while other was more informal such as the fruits of hard-won experience. But regardless of whether formal or informal, most organizations really struggle to capture, share, and cultivate the collective working knowledge of the organization."
He said this is particularly true for frontier functions like engineering, marketing, and sales that operate at the edge of institutional knowledge. "They have an insatiable demand for the latest and greatest information to win the next deal, fend off competitors, captivate customers and inspire innovation," he said. "As often as not, the information they need to win the day exists, it just isn't available when it matters."
Wahbe said Highspot is following the lead of existing Internet solutions like Google, Amazon and Pinterest. "They all use similar pioneer techniques to connect people with information–they use machine learning," he said. "Compare those Internet solutions to existing enterprise search solutions for business. They don't use machine learning, they use tags. However, tags get less and less correct and less and less relevant over time."
The Highspot approach to enterprise search is based on four pillars: to leverage approachable consumer user experiences, to build a comprehensive knowledge graph, to increase relevance through machine learning, and to deliver it all as a modern cloud service.
"To effectively 'know what you know,' Highspot must cast the broadest possible net for information, and gracefully incorporate content wherever it is created, whatever its type, and wherever it is consumed," Wahbe said in his post. "We are committed to integrate with information wherever it resides, including widely used platforms such as Office 365, Google Apps, Box, Dropbox, and Salesforce as well as information types as diverse as documents, presentations, spreadsheets, images, videos, audio, news feeds and news alerts."
Highspot leverages familiar consumer Web experiences and it increases relevance through advanced machine learning. The machine learning platform delivers highly relevant results that get even more relevant over time, Wahbe said.
With machine learning, as people use Highspot the knowledge graph gets smarter. Highspot enables users to organize information in "Spots," which are collections of related content. "Spots are the main ways we organize knowledge," Wahbe said.
The Highspot knowledge graph represents all people and all items in an organization and all the relationships between them. The knowledge graph factors in observed facts such as geography, views, likes and follows, as well as learned facts such as influence, similarity, trending and interest, Viola said.
"I try to put things in front of you that will be of value to you," he noted.