Founded 2013 | HQ Philadelphia, PA | 160 employees (est.) | $<20M revenue (est.)

We like Guru and applaud its ambition and success to date. … If it can become the centralized knowledge hub across the information stack, it stands a decent chance of long-term success. But that is a challenge, and one recognized by the company.

The Company

Guru Technologies, Inc. was founded by CTO Mitchell Stewart and CEO Rick Nucci in 2013, and the firm is headquartered in Philadelphia, Pennsylvania with a second office in San Francisco, California. Currently on Series C funding, Guru has raised $70.7 million from investors like Accel, FirstMark, Emergence, and Thrive Capital. As of April 2021, Guru has over 1,000 customers including Shopify, GitHub, and Spotify.

The Technology

We position Guru as a Knowledge Network, or Knowledge Automation Platform, providing a single source of truth for corporate information. However, it is typically deployed in three main situations: to support customer service by providing accurate product information, to streamline employee onboarding, and to facilitate internal communications.

What this means in practice is that information fragments are stored in a single cloud database run by Guru. Once stored there, the information is automatically analyzed for relevant content and, over time, usage patterns associated with the various information fragments. In turn, as the system leverages analytics and machine learning (ML), it can suggest relevant content in context to the end user.

The information fragments are captured from wikis, intranets, and collaboration systems. Users can also directly upload information in the form of spreadsheets, web browsers, documents, text, images, and videos. The information, once analyzed, is surfaced via a web browser or through integrations with applications like Zendesk, Slack, or Confluence Cloud. Suggestions can also be surfaced in chat tools or email. Of particular interest here is Guru’s ability to monitor voice interactions and surface relevant suggestions based on those conversations. It is also possible to map knowledge so that it surfaces in specific teams or webpages.

What we have here, then, is Knowledge Management reinvented. The traditional tools of KM – capturing knowledge, managing it, and making it available – are supplemented by strong push capabilities and strong reporting based on usage patterns.
Just like traditional KM tools, Guru makes use of a search capability (based on Elastic Search). Over time, through the use of ML, it adapts to further influence the sorting of search results based on the information the system has learned about you as a user, your rights to access, and your interests.

From an end-user perspective, Guru leverages the concept of “cards” for sorting, accessing, and managing knowledge sources (see Figure 1). Cards can be tagged and verified, synced to an outside source, and sorted by topic, teams, or boards. The combination of basically manually managed cards with AI-supported suggestions seems a solid one.

Finally, it is important to note that Guru is used less as a replacement system and more as an augmentation layer on top of your existing systems, bringing relevant, accurate, and timely knowledge into employees’ workflows. So, rather than ripping and replacing the information silos within a traditional intranet or within employee communication and productivity systems like Slack, Teams, or Salesforce, it integrates with what is already there. Hence, it has developed a strong set of over 30 connectors and APIs to commonly used business systems.

Figure 1
Example of Guru’s Card System

Our Opinion

We like Guru and applaud its ambition and its continued success to date. We particularly like the blend of old school methodologies such as cards with advanced machine learning technologies, which makes the system familiar and easy to use out of the box but ever smarter and more efficient as the knowledge base grows. If it can become the centralized and trusted knowledge hub across the information stack within organizations, it stands a good chance of long-term success as such systems are extremely sticky.

Advice to Buyers

If you are a knowledge-centric firm, at least consider trialing Guru, even if you have already tried other KM tools without success. On the surface, there is a relatively straightforward KM system, but it is one with hidden depths that grow significantly in value over time. You do need to give it a real shot at success by committing to upload a decent body of knowledge from the get-go to see if it is a match for your specific needs. Though in theory the product is of use in any firm, we think it will find its sweet spot in organizations with physically remote or hybrid knowledge workers, to create productive connections between individuals and teams.

SOAR Analysis


  • Updated approach to KM
  • AI-driven suggestions
  • User-friendly approach


  • Become the core hub of dynamic KM within organizations
  • Become the de facto standard approach to KM
  • Further leverage AI & ML


  • Partnership with Slack/Salesforce
  • Partnerships with other info-centric apps
  • Industry-specific templates


  • 1,000+ customers in just eight years
  • Key partnerships
  • Raised substantial capital

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