Unlock Enterprise Knowledge with Atlassian Rovo

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Unlock Enterprise Knowledge with Atlassian Rovo

In today’s fast-paced business environment, knowledge is power – but only if you can access it at the right time. Organizations generate terabytes of data and documentation, but much of that valuable knowledge remains locked away in disparate systems. How often have you thought: “We must have something on this topic somewhere in our company,” only to spend hours searching multiple tools without finding the answer? Atlassian Rovo is designed to solve exactly this problem by unlocking enterprise knowledge and putting it at every team member’s fingertips.

This article explores how Atlassian Rovo helps enterprises find answers, glean insights, and act on information across all their apps and services. We’ll look at Rovo’s powerful search capabilities, its AI-driven understanding of context, and how it turns information into action. By the end, you’ll see why Rovo is not just an incremental improvement, but a leap forward in enabling data-driven decision making and collaboration.

The Pain of Information Overload in Enterprises

Let’s set the stage: Enterprises today use a multitude of software tools – project trackers, knowledge bases, communication platforms, cloud drives, CRM systems, the list goes on. Important information is scattered everywhere. It’s no surprise that nearly half of digital workers struggle to find information needed to do their jobs​. Critical knowledge gets trapped in Confluence pages no one remembers, in old email threads, or buried in the comments of a Jira ticket. The result is information overload on one hand and information scarcity on the other – employees are drowning in data but still can’t find what they need.

This fragmentation leads to delays, repeated work (because if you can’t find it, you redo it), and frustration. It also poses a risk: decisions might be made with incomplete information simply because the person making the decision wasn’t aware that the knowledge existed elsewhere in the organization.

What if your team could instantly search everything your company knows about a project or topic, in one place? That’s the promise of Atlassian Rovo. It uses Generative AI and a unified index of your enterprise data to make searching as easy as asking a question.

Unified Search: One Question, Every Answer You Need

Atlassian Rovo introduces a unified search experience that reaches across both Atlassian and third-party apps. Rovo Search is not limited to a single database or tool - it operates over a federated index that spans Jira issues, Confluence pages, Atlas projects, Bitbucket repos, as well as content from external connectors like Google Drive, Slack, Microsoft Teams, GitHub, ServiceNow, and many others​. In essence, Rovo acts as an enterprise-wide search engine, powered by AI understanding.

Consider a scenario: You want to know “What is the status of Project Neon and who’s working on it?”. In a normal setup, you might have to: search Confluence for a project page, check Jira for open tickets, maybe look at a roadmap in Atlas, and message a colleague who was involved. With Rovo, you simply ask that question in one place. Rovo will parse your query and might return an aggregated answer such as:

• A summary: “Project Neon is in Phase 2, on track for Q3 launch.”
  
  
• Key details from multiple sources: perhaps the latest update from the Confluence project page, combined with progress stats from Jira.
  
  
• A list of team members or the project owner (pulled from Atlas or Jira).
  
  
• Relevant documents: links to the project plan or design specs.
  
  
• Follow-up questions: “Do you want to see the risk register?” or “Who are the stakeholders?”.
  
  

This isn’t a fantasy - it’s the kind of contextual result Rovo Search is designed to deliver. According to Atlassian, Rovo surfaces the most contextual and relevant results, no matter where the data is stored or what format​. It understands the intent behind your search, not just literal keywords.

How Rovo Search Unlocks Knowledge

Natural language understanding: You don’t need to craft boolean queries or know exact filenames. Rovo accepts natural language queries. You can ask complex questions directly. For example: “What was our customer satisfaction (CSAT) score for Project X last quarter?”. If that data is in a report on Google Drive or an entry in Jira, Rovo will fetch it​. Or you might ask, “Who is Jane Smith and what does she work on?” – Rovo can identify Jane Smith (maybe an employee profile page or an Atlas profile) and return a knowledge card about her, including her role and current projects​.

Cross-tool connections: Rovo doesn’t stop at listing results – it draws connections. Suppose you search for a client name that appears in multiple systems. Rovo might show you a Confluence page describing the client engagement, and related Jira issues tagged with that client, and a Salesforce record (if integrated) – all together. This cross-referencing is powered by Atlassian’s teamwork graph which understands relationships between pieces of data (projects, people, goals, etc.)​. Essentially, Rovo is building a web of knowledge behind the scenes so that one query can traverse that web and bring you a 360° answer.

Enterprise-wide connectors: A standout feature is Rovo’s connectors. Atlassian has built-in connectors for dozens of third-party products – from file storage like Box and Dropbox to productivity suites like Office 365, communication tools like Slack, development platforms like GitHub/GitLab, and even legacy or on-prem systems like Confluence Data Center​. By enabling these, an admin lets Rovo index content from outside Atlassian and merge it into search results. For example, you could retrieve a Slack conversation snippet in the same search as a Confluence page. The result is a single source of truth search. Instead of performing separate searches in each tool, Rovo aggregates knowledge across all connected sources.

• Internal linking tip: Make sure to visit Atlassian’s documentation on available Rovo connectors to see the growing list of apps you can integrate. The more sources connected, the more complete Rovo’s knowledge becomes.
  
  

Speed and relevance: Rovo is designed to give answers “in a heartbeat”​. Under the hood, it pre-indexes your content so search is fast. Moreover, it ranks results by contextual relevance. That means if you search a project name, the official project page might rank higher than a passing mention in a random document. Rovo’s AI can determine what you’re likely looking for. It even can highlight “actionable results” – for instance, if your query suggests you need to do something (like “How do I request PTO?”), Rovo might highlight the HR policy page and even extract the key steps for you​.

Example – Consolidating Knowledge: Let’s say an IT manager searches for “quarterly security audit results”. Without Rovo, those might be in an email, or a PDF attached in Confluence, or a Jira ticket. With Rovo:

• It could find the Confluence page where Q2 security audit outcomes are documented.
  
  
• It might also find a Jira issue where an action item from the audit is tracked.
  
  
• It could retrieve a link to an external compliance report on SharePoint.
  
  
• It would present a quick summary if available (e.g., “Audit XYZ: 3 minor findings, all resolved”).
  
  
• It respects that only IT managers or security team should see this – if a random engineer searched this and didn’t have permissions, they might get no results or a limited summary (thus maintaining confidentiality)​.
  
  

By delivering all that in one go, Rovo truly unlocks that knowledge for the person who needs it, right when they need it.

Knowledge Cards and Definitions: In-Context Insights

One of Rovo’s clever features to help you learn as you search is its use of knowledge cards and definitions. These are dynamic, context-aware snippets that Rovo can display on the side, enriching your understanding of a topic without requiring extra clicks.

For example, if you search a person’s name, Rovo might show a people card with that person’s title, department, recent projects, and contact info​. It’s pulling this data from your company directory or Atlassian Atlas profiles. This helps you quickly glean who someone is, their expertise, and what they’re working on – useful for large enterprises where you might not know colleagues in other departments.

Another scenario: corporate jargon and acronyms. Every large organization has its alphabet soup of acronyms or code names (e.g., “PTO”, “OKR”, project codenames). If you encounter a term you don’t recognize, Rovo can help define it. Rovo will automatically highlight acronyms or terms in Confluence pages or Jira issues that it believes have definitions​. You can click on a highlighted term, or manually ask Rovo “What is XYZ?”, and it will search for a definition. How? Often, companies keep glossaries or FAQ pages (say, a Confluence page listing common acronyms). Rovo will find the relevant entry and show it as a definition card​. If it’s missing or not quite right, you can contribute by adding a definition for that term for future users​. This way, Rovo acts as a living glossary, demystifying company-specific language. Atlassian notes that when they trialed Rovo internally, over 75% of employees said Rovo helped them understand unfamiliar acronyms​ - a testament to how valuable this feature is in knowledge sharing.

Knowledge cards aren’t limited to people or terms. They could be for projects, goals, or other entities. For instance, searching a project name might show a card summarizing the project status (pulled from Atlas or a Jira epic), key dates, and team members. Searching a goal or OKR could bring up its latest progress metric. These cards provide at-a-glance information without requiring you to open the source document right away.

This means Rovo not only finds information, it helps explain and contextualize it. Especially for new employees or cross-functional collaboration, these quick insights are invaluable. They reduce the learning curve and ensure that important context (like “what does this abbreviation mean?” or “who owns this system?”) is always within reach.

Conversational Exploration with Rovo Chat

In addition to the search interface, Rovo offers a conversational interface (Rovo Chat) that plays a big role in unlocking knowledge. Why have chat in addition to search? Because sometimes you don’t even know the exact question to ask upfront. With a conversation, you can start somewhere and let the AI guide you to the info through follow-ups.

Rovo Chat allows you to query knowledge in a more exploratory, interactive manner​. For example, you might start by asking, “Tell me about Project Phoenix.” Rovo might give a summary. Then you can follow up with, “Who is working on it?” and it will list the team. Then, “Show me the latest design mockups,” and if those are in, say, Figma or attached in Confluence, Rovo can dig that up. This back-and-forth Q&A is a powerful way to iteratively uncover knowledge – much like you’d do when consulting an expert.

Rovo Chat is particularly useful for complex research questions or brainstorming. Let’s say you’re writing a strategy document and you need to gather various pieces of info: last quarter’s sales figures (from a spreadsheet), major incidents that affected a product (from Jira/Opsgenie), customer feedback highlights (from Jira Service Management or Zendesk). You can ask Rovo in a conversational flow:

• “Give me a summary of customer feedback on product X in the last 6 months.”
  
  
• “Ok, what were the top complaints? And how did we address them?”
  
  
• “Were there any major outages or incidents in that period? Briefly summarize them.”
  
  
• “What were our sales numbers each quarter?”
  
  
• “Great. Now draft a section combining these insights for my report.”
  
  

Rovo can handle this sort of multi-step request, pulling data from different sources and even generating text based on it. It essentially lets you chat with your company’s knowledge base. And because it remembers context, you don’t have to repeat the subject – your second question “what were the top complaints?” would be understood as referring to the customer feedback you just asked about.

All of this happens without leaving Confluence or Jira (or whatever Atlassian product you’re using). Rovo Chat slides out in a sidebar, so you can still see the page or issue you’re working on. This means as you discover insights, you can immediately apply them – for instance, updating the page you’re on with the new info, or creating a Jira ticket based on the chat (Rovo can help with that via actions).

Another advantage: Rovo Chat can leverage plugins and actions to do more than just talk​. For example, within the chat you might see an option like “Save this to Confluence” or “Create a Jira task from this answer”. Rovo uses what Atlassian calls actions to carry out such tasks, always asking you to confirm before doing it​. This tight integration shortens the path from finding knowledge to using knowledge.

So, why is conversational AI key to unlocking knowledge? Because it lowers the barrier to entry. Not everyone knows how to formulate a search query to get what they need, but anyone can ask a question. And not everyone even knows what they need until they talk it through. Rovo Chat lets employees have that dialogue, and the AI fills in with information from the collective brain of the company.

For enterprise users, this means a new way of working: Instead of scouring wikis and spreadsheets for hours, you can have a 5-minute conversation with Rovo and gather all the intel you need. It’s like having a super-informed assistant who can recall any document or data point on demand.

From Information to Action: The Role of Rovo Agents

Unlocking knowledge isn’t just about retrieval – it’s also about acting on that knowledge effectively. This is where Rovo’s “Act” capability comes in, primarily through Rovo Agents. While we have a dedicated article on Rovo Agent (see “Rovo Agent” for an in-depth look), it’s important to touch on how Agents contribute to unlocking enterprise knowledge.

Rovo Agents can be seen as specialized AI coworkers that not only use the knowledge in your systems but also apply it to perform tasks. For instance, consider an agent that is tasked with ensuring project pages are up to date. It has access to all project data (from Jira, etc.) and can proactively update Confluence pages with the latest status, or ping owners if something is missing. In doing so, it’s making sure that the knowledge base (the Confluence project pages, in this case) stays current and accurate – which in turn helps everyone find correct information.

Another example: an “Ops Guide” agent in IT could automatically pull in relevant troubleshooting steps when an incident ticket is created, essentially unlocking the knowledge from past incidents and presenting it to engineers in real time. This agent could search through past post-mortems or knowledge base articles whenever a new issue comes in, saving the team from searching manually.

What Rovo Agents do is operationalize knowledge. They can take what’s known (data, documents, best practices) and inject it into workflows at the right moment. This ensures that knowledge is not just sitting in a repository, but actively used to streamline work.

A few ways Agents unlock value:

• Automation of knowledge-based tasks: E.g., an agent that reviews documents for compliance can automatically flag issues or add missing info by referencing the policy documents (knowledge) and applying them to the draft (action).
  
  
• Consistency and best practices: Agents can be configured with company best practices. For example, a “PRD Assistant” agent can enforce that every Product Requirements Doc includes sections A, B, C (it knows this from a template or guideline). It can fill in portions or prompt the author for missing pieces. This means the collective best-practice knowledge of your organization is upheld every time, without relying on each author to remember everything.
  
  
• Bridging systems: Agents can integrate multiple systems in a workflow. A “Customer Success Agent” might combine data from CRM, support tickets, and engineering bugs to create a unified customer issue report. Without the agent, an employee would manually gather that info from three places. The agent has the knowledge of how to fetch and compile it, doing it much faster.
  
  

By employing Rovo Agents, enterprises ensure that knowledge flows to where it’s needed without manual effort. They act as conduits and facilitators of knowledge, automating the mundane so human teams can focus on interpretation and decision-making.

Of course, with great power comes the need for control. Enterprise admins can govern how and where Agents are used​. You might start with a few out-of-the-box agents in non-critical paths, measure the results, and then expand. Rovo provides an Agents in automation feature which allows some agents to run automatically (with admin oversight) for truly hands-off operations​. The key is that Agents will always either require a user’s confirmation or an admin’s setup to run - they won’t go rogue.

Actionable Insights for IT Leaders and Teams

For IT leaders, unlocking enterprise knowledge with Rovo isn’t just a tech initiative, it’s a strategic one. Here are a few actionable considerations:

• Identify high-friction search areas: Talk to your teams about where they lose time looking for info. Is it technical documentation, HR policies, client info, or something else? Pilot Rovo in those areas first. For example, integrate your top 5 third-party systems that house that info. Measure the reduction in search times or support tickets asking “where is X?”.
  
  
• Leverage Rovo for onboarding: New hires typically spend weeks learning who’s who and where things are. By giving them Rovo from day one, you enable them to ask questions freely. Encourage them to use Rovo Chat to learn about acronyms or project histories. This can drastically cut down onboarding time as they become self-sufficient in finding information.
  
  
• Promote a culture of documentation and curation: The value of Rovo’s answers depends on the data it has. This is a great time to encourage teams to document their work in Confluence, to tag pages properly, and to connect relevant tools. Knowing that a powerful search will index their content, teams might be more inclined to keep that content well-structured. Additionally, you might establish a practice of adding definitions for new jargon in Rovo (via the definitions feature) so that the next person who searches sees a useful explanation​.
  
  
• Monitor and refine: Use whatever analytics Atlassian provides (or simply gather feedback) to see what people are asking Rovo and if the answers are helpful. You might discover, for instance, many people asking questions about a certain internal process – if Rovo isn’t answering well, that’s a signal to improve the documentation of that process, or to tweak connector settings. The goal is to continuously improve the organization’s knowledge accessibility.
  
  

For developers and technical teams, think about how you can extend Rovo’s knowledge unlocking:

• Can you feed it additional data sources (perhaps through custom connectors or by mirroring data into an Atlassian-friendly format)?
  
  
• Can you create an internal Agent that encapsulates a complex procedure? For example, a DevOps agent that knows how to fetch logs from your system, parse them, and highlight errors could save tons of time for engineers troubleshooting issues.
  
  
• Also consider governance: put guardrails on which repositories or spaces Rovo indexes if needed (especially during trial phases) to limit scope to non-sensitive data, then expand as confidence grows.
  
  

A New Era of Informed Decision-Making

By unlocking enterprise knowledge, Atlassian Rovo essentially democratizes information. The knowledge that was once siloed among specific team members or hidden in obscure systems is now available to anyone who needs it, when they need it (assuming permissions allow). This can have profound effects:

• Faster decisions: When leaders can quickly gather all pertinent data, they can make decisions without waiting days for a report.
  
  
• Innovation: Employees can discover insights that spark new ideas – for instance, finding a past project’s approach to a similar problem, and building upon it rather than starting from scratch.
  
  
• Employee empowerment: People feel more confident and autonomous when they can self-serve information. It reduces dependency on “that one person who knows X”, relieving bottlenecks.
  
  
• Cross-team collaboration: Rovo might surface connections between teams. A designer searching for research on “mobile user onboarding” might stumble upon a document by the support team about user onboarding issues. Such serendipity can lead to cross-pollination of ideas and better alignment.
  
  

To ensure SEO optimization for those interested in this topic: Atlassian Rovo is frequently described as an “AI-powered enterprise search and knowledge discovery tool” or “generative AI for enterprise knowledge management”. It’s part of the broader Atlassian Intelligence initiative combining open AI models and Atlassian’s data graph​. If you’re researching solutions in this space, you might also encounter terms like enterprise search engines, AI chatbots for internal knowledge, or virtual assistants for teams – Rovo essentially encompasses all of these in one platform.

Thought-Provoking Question

Ask yourself: If every employee in your organization had on-demand access to all organizational knowledge, how would that change your business outcomes? Would projects execute faster? Would customer issues be resolved more efficiently? Would fewer mistakes be made due to ignorance of existing information? These are the kinds of benefits unlocking knowledge can bring.

Atlassian Rovo is a tool - a very powerful one - to achieve those benefits. It breaks open the silos and brings a company’s collective brainpower to each individual. The companies that thrive will be those that leverage their knowledge effectively, and Rovo is one path to doing so.

Rovo use cases - https://www.atlassian.com/software/rovo/use-cases

Rovo connectors - https://www.atlassian.com/software/rovo/connectors

In conclusion, unlocking enterprise knowledge is no longer an unattainable ideal. With tools like Atlassian Rovo, it’s here and now. The organizations that capitalize on it will turn their wealth of information from a burden into a strategic asset. Don’t let your knowledge remain locked up - unleash it with Rovo and watch your teams soar with insight.