Rovo vs. Competitors: A Technical Comparison

Modern enterprises are spoiled for choice when it comes to AI-powered productivity tools and enterprise search. Atlassian’s Rovo has emerged as an AI “teammate” designed to unlock organizational knowledge, but how does it stack up against other major players? In this blog, we compare Rovo with Glean, Microsoft 365 Copilot, and Google’s Workspace AI offerings. We’ll look at their technical capabilities, integration depth, data security approaches, and total cost of ownership, and discuss why Rovo’s approach to enterprise search and knowledge discovery differs from its competitors, and when an organization might choose Rovo over the alternatives.

Key areas of comparison include: feature-by-feature capabilities, integration breadth, security and compliance, and pricing models. By the end, you should have a clearer picture of which solution fits which scenarios, and how Rovo’s unique approach stands out in this competitive landscape.

Feature-by-Feature Comparison

• Atlassian Rovo: Rovo is an AI-powered platform with three core components: Rovo Search, Rovo Chat, and Rovo Agents. Rovo Search performs semantic enterprise search across both Atlassian tools and third-party apps, surfacing relevant results in one place. Rovo Chat acts as a context-aware virtual teammate that can answer questions using your organization’s data, via Atlassian’s Teamwork Graph. Rovo Agents are AI-driven automations that can perform tasks, with 20+ out-of-the-box agents and the ability to build custom agents with no code. This combination lets users find information, get answers, and even take actions all through a unified AI assistant.

• Glean: Glean is an AI-driven enterprise search and “Work AI” platform that aims to act as a universal search engine for all your company’s knowledge. It connects to 100+ business applications and indexes their content to provide comprehensive search coverage. Glean’s standout features include generative AI-powered summaries of documents and a built-in knowledge graph that maps relationships between people, content, and activity to personalize results. The search results are updated in real-time and always respect each user’s permissions. Glean also offers an AI chat assistant and even an agents framework, though its customizability via no-code options appears more limited than Rovo’s. Overall, Glean’s focus is on deep search relevance and AI insights across a broad array of enterprise tools.

• Microsoft 365 Copilot: Copilot is Microsoft’s AI assistant embedded across the Office 365 suite, including Word, Excel, PowerPoint, Outlook, Teams, and more. It leverages OpenAI’s GPT-4 model combined with your organization’s data in the Microsoft Graph to perform tasks like drafting documents, summarizing email threads, creating presentations, analyzing data in spreadsheets, and answering natural-language questions about your business content. Within the Microsoft ecosystem, Copilot behaves like a virtual executive assistant: you can ask it to recap meeting notes, generate a first draft of a document, or find information across your emails and SharePoint. While Microsoft also offers a free web-based Copilot, the enterprise Copilot is tightly integrated with M365 apps and business data, operating with enterprise-grade security inside your tenant. Copilot also introduced “Business Chat,” which can combine data from across the Microsoft 365 environment to answer queries. However, Copilot’s functionality largely lives within Microsoft’s own apps; it excels at making Microsoft-centric workflows more efficient, but less so at searching third-party tools.

• Google Workspace AI (Duet AI and Agentspace): Google’s approach to AI in the enterprise has two facets. First, Duet AI for Google Workspace provides generative assistance within Gmail, Google Docs, Sheets, Slides, and Meet. Duet can draft emails, brainstorm content in Docs, create visuals in Slides, take meeting notes, and help summarize or answer questions based on content in your Google Drive. This is Google’s parallel to Microsoft’s Copilot, embedded in Google’s productivity apps. Second, Google has introduced an enterprise search and AI agent platform that extends across Workspace and beyond. Google’s enterprise search tools let users query across Gmail, Drive, Calendar, etc., and even some third-party sources, with natural language. Early previews of Google’s Agentspace show it can connect to apps like Atlassian Jira and deliver AI-powered search results and even multi-step “agentic” actions. In essence, Google is combining its renowned search capabilities with new generative AI features. While Google excels in search quality, its enterprise AI assistant is still emerging. Initial users found Google’s AI slightly better at pure search and suggesting next steps, whereas Atlassian’s Rovo was more mature in workflow integration when both were tested side-by-side.

Integration Capabilities and Ecosystem Support

One of the biggest considerations is how well each tool integrates with the rest of your software stack. On this front, Rovo and Glean distinguish themselves by their breadth of third-party connections, while Microsoft and Google leverage their native ecosystems with selective extensions.

Atlassian Rovo was built with an “open” philosophy despite being part of Atlassian’s ecosystem. It can serve as a single search hub for dozens of external apps. Out-of-the-box, Rovo comes with 50+ built-in connectors to popular SaaS platforms beyond Atlassian. These include productivity and collaboration tools like Google Drive, Gmail, Outlook/Exchange, Microsoft Teams, Slack, Box, Dropbox, Notion, and Trello; development tools like GitHub, GitLab, Bitbucket, and Jira Service Management; project management apps like Asana and Monday; CRM tools like Salesforce and HubSpot; ITSM and monitoring tools like ServiceNow, Docusign, and PagerDuty; and many more. This breadth means Rovo can index and unify information across essentially all the places your work happens, not just inside Atlassian. Moreover, these connectors come with built-in permissions management, so Rovo automatically respects the access controls of each source system when retrieving data. Within Atlassian’s own suite, integration is seamless: Rovo’s AI features are embedded directly in the interfaces. This tight embedding allows Rovo not only to search and read data but also to take actions in context. Rovo’s integration depth is a major advantage for organizations using Atlassian heavily, and even those with a heterogeneous toolset; it aims to break down silos between tools by connecting them into a “system of work.”

Glean, as an independent platform, also shines in integration breadth. Glean provides connectors for over 100 applications, covering a wide range of business tools. These include many of the same apps Rovo covers, as well as knowledge bases like Confluence or Notion, and ticketing systems like Zendesk or Jira. Glean’s philosophy is to meet the user wherever knowledge lives; it even offers integrations into daily workflows like a browser extension and plugins for Slack or Teams chat to query Glean directly. However, because Glean isn’t natively part of any of those platforms, using it often means switching to a Glean interface to perform a search, then clicking through results. Rovo, in contrast, can surface answers directly inside Atlassian tools and even perform actions there. One specific differentiator is Rovo’s no-code custom agents that can be easily shared across teams; Glean has an “Agent” framework too, but building complex automations on Glean might require more technical setup or their provided templates. In short, Glean casts a wide net of integrations and is a strong choice if your organization’s data is spread across many non-Atlassian systems, but it may introduce another separate layer for users to log into. Rovo’s integrations are slightly fewer in count but very well-integrated into daily workflows, especially if you’re already on Atlassian Cloud.

Microsoft Copilot primarily integrates within the Microsoft ecosystem by design. It is embedded in Microsoft 365 applications and surfaces your data from Microsoft-centric sources: Outlook emails, Teams chats, OneDrive and SharePoint files, meetings on your calendar, etc. Microsoft does provide a framework called Graph Connectors which can connect external systems to Microsoft Search; for example, there are connectors to bring in content from Confluence, Jira, or Salesforce into the Microsoft 365 search index. This means that in theory, Copilot could answer questions that involve Atlassian data or other third-party content if those connectors are set up. In practice, setting that up requires IT effort and may not cover as many apps as Rovo or Glean do out-of-box. Microsoft has shown demos of Jira integrated with Teams and Copilot for developers, and it acquired an AI company to improve enterprise search across disparate systems. Still, Copilot’s “home field” is Microsoft 365; organizations deeply invested in Microsoft’s ecosystem will benefit from seamless AI inside Office docs and emails. But if your knowledge base spans various SaaS tools, Copilot alone might not unify them without additional services. In our comparison, one enterprise user noted that using Rovo instead of Copilot for cross-app search eliminated a lot of context-switching: they didn’t have to jump between apps or manually feed data to Copilot, because Rovo’s one-stop search already spanned everything in one query window.

Google’s Workspace AI similarly integrates best with Google’s own applications. Duet AI is built into Gmail, Google Docs, Slides, Meet, etc., so it naturally has access to everything in your Google Workspace with no extra configuration. For broader enterprise search, Google’s new Agentspace platform is introducing connectors for some external tools. However, as of early 2025, these connectors were in preview and required admins to manually configure permissions mappings for third-party data. Google Cloud Search could index a variety of data sources, but it was mainly adopted by Google-centric organizations. A strength for Google is that nearly every knowledge worker is familiar with the power and simplicity of Google’s search interface; bringing that experience to enterprise data is compelling. In testing, Google’s AI search responses were slightly ahead in pure search relevance, but Atlassian’s Rovo had stronger native ties into workflow. If your company lives in Google Workspace, Duet AI will effortlessly enhance productivity within those apps. But if you need a federated search across many systems, Google’s solution is still catching up to the likes of Rovo and Glean in connector breadth.

Security and Compliance Differences

When deploying an AI that touches all your company’s knowledge, data security and privacy are paramount. All these solutions address security, but there are nuances in their approaches and trust models:

• Atlassian Rovo: Rovo is built on Atlassian’s trusted cloud platform, inheriting the rigorous security measures and compliance certifications Atlassian offers. All data indexed by Rovo is stored within Atlassian’s cloud infrastructure, and Rovo strictly respects your existing permissions on each content source. In practice, that means an employee using Rovo will only see search results they are allowed to see in the original tool: if a Confluence page or Google Drive file is restricted from them, Rovo’s AI will not surface its contents. Rovo also supports encryption in transit and at rest, and since it’s part of Atlassian Cloud, it benefits from Atlassian’s partnership with AWS for secure data hosting. One differentiator is Atlassian’s Teamwork Graph: by grounding AI responses in a graph of your organization’s verified data, Rovo helps minimize AI hallucinations and ensures answers are traceable to real sources. Essentially, the graph acts as a guardrail for the LLM behind Rovo, improving both relevance and trustworthiness of results. For companies already comfortable with Atlassian Cloud’s security, extending that trust to Rovo is straightforward, no additional third-party vendor handling your data.

• Glean: Glean is a third-party SaaS provider, so using it involves granting it access to your various data sources. Glean was “secure by design from day one,” and they emphasize robust enterprise security features. Content ingested into Glean’s index is protected, and Glean also respects the source systems’ access controls. Glean likely maintains industry-standard encryptions and has its own compliance attestations. One consideration is data residency and control: Glean will store indexed copies of your documents in its search index. Some companies with strict data governance might prefer solutions that let data remain in-place. According to one analysis, Glean’s indexing of non-public content upfront could raise questions for highly sensitive info, but in general Glean takes precautions to secure that indexed data. In summary, Glean has strong security and permission controls, but as with adopting any new vendor, organizations need to vet it for compliance with their requirements. Lack of an on-premises option means highly regulated orgs must be comfortable with Glean’s cloud.

• Microsoft 365 Copilot: Microsoft has built Copilot with enterprise-grade security, privacy, and compliance at its core. All the AI processing for Copilot for Microsoft 365 happens within your Microsoft 365 tenant: the data fed to the model and the responses generated are not used to train broad public models, and they do not leave your controlled environment. Microsoft leverages the fact that your data already lives in their cloud and simply layers AI on top. Notably, Microsoft’s approach to privacy is that Copilot does not introduce new storage of data beyond what’s in Microsoft Graph; it accesses data on the fly with your permissions. Microsoft also has perhaps the longest track record with enterprise compliance among these, covering just about every certification needed for cloud services. For many IT leaders, having Copilot essentially inside the Microsoft security boundary is reassuring: it’s an add-on to an already-approved platform. If Copilot connects to external systems via Graph connectors, those external data may be indexed in Microsoft’s search index, so similar diligence is needed as with any enterprise search. But generally, if your data is predominantly in Microsoft 365, Copilot doesn’t pose additional risk. Microsoft also implemented Bing Chat Enterprise such that no conversation data is leaked or used outside your org. In short, Copilot aligns with the zero-trust and compliance standards large enterprises expect, with the convenience that it’s under Microsoft’s umbrella where many companies already have trust.

• Google Workspace AI: Google’s Duet AI inherits Google Cloud’s robust security infrastructure. Data from your Gmail, Docs, Drive, etc., when used by Duet, is not used to train Google’s models on the public side; it’s only used to give you output and then is discarded, according to Google’s assurances. Google Workspace has enterprise certifications similar to Microsoft, and Google has long experience managing cloud data securely for its customers. When extending to Google’s new Agentspace, Google allows connections to other systems but requires explicit admin setup of those integrations and permission scopes. This means you have granular control over what third-party data Google’s AI can see. Companies that partner with Google often trust its prowess in data protection, though some are cautious given Google’s business model in other areas (advertising). It’s worth noting that Google Cloud Search let admins decide which repositories to index, and all data indexed was stored encrypted on Google’s servers. As Google adds generative AI, it will likely maintain those strict boundaries. One possible weakness is that Google’s knowledge graph about your organization might not be as rich as Atlassian’s Teamwork Graph for non-Google content. But from a compliance perspective, Google’s AI tools meet the needs of most enterprises and are backed by Google’s investments in privacy. In summary, if your company is already using Google Workspace securely, turning on Google’s AI features keeps you in that same trust boundary. As with others, due diligence is needed when connecting any additional data sources.

Pricing and Total Cost of Ownership

The financial aspect is where these solutions diverge significantly. How much will each cost you, and what is the total cost of ownership when considering licensing and existing subscriptions? Let’s break down the pricing models:

Atlassian Rovo’s pricing has evolved rapidly as Atlassian tries to accelerate adoption. Initially, Rovo was offered as a paid add-on (around $20–$24 per user/month for large teams). However, Atlassian recently shifted to bundle Rovo into its core cloud plans. As of early 2025, Rovo’s Search, Chat, and Agents features are being included at no extra charge for Atlassian Cloud Premium and Enterprise customers, and even Standard plan users will get it later in the year. In other words, if your organization has an Atlassian Cloud subscription, Rovo comes built-in. For organizations not on those tiers, Atlassian plans to offer Rovo at a nominal fee for standalone use. This bundling strategy means the incremental cost of Rovo is effectively $0 for many Atlassian customers; it’s now part of the platform. The total cost of ownership for Rovo, then, is primarily your Atlassian subscription itself. There might be some initial implementation effort, but there isn’t a separate vendor contract or large additional fee. This makes Rovo extremely cost-competitive, especially when compared to the high per-user costs of others. Atlassian’s reasoning is that bundling AI will drive usage and value across its tools, and it lowers the barrier of having to justify a separate AI expense. So, if you’re already an Atlassian customer, you can potentially replace a paid enterprise search subscription with Rovo and save money.

Glean’s pricing is at the opposite end; as a specialized third-party solution, it commands a premium. Glean does not publicize standard prices, instead offering custom quotes, but reports indicate it typically costs around $30 to $50 per user per month for its full AI search capabilities. Enterprise contracts can run into hundreds of thousands of dollars annually, especially when including all features and premium support. For example, a 100-user deployment might cost in the mid-six-figures per year. In addition to seat licenses, some customers have noted additional support fees (~10% of contract) and annual increases if usage grows. In short, Glean is a significant investment. Its total cost of ownership includes not just the subscription, but also the effort to implement it (often requiring a pilot project, since no free trial is available). That said, organizations that choose Glean are often those that need its advanced capabilities across many silos and may justify the cost with productivity gains. It’s worth comparing that if you already pay for Microsoft or Atlassian tools, Glean’s cost is on top of those, which can make ROI calculations tricky for buyers. The lack of transparent pricing can also make it harder to budget. Therefore, Glean might be best suited for larger enterprises with pressing knowledge management pain points and the budget to address them. Otherwise, the free or included options from bigger platforms might be attractive alternatives.

Microsoft 365 Copilot’s pricing is relatively straightforward: Microsoft has set it at $30 per user per month (when added to a Microsoft 365 Enterprise subscription). This price is in addition to whatever you’re already paying for Office licenses. Copilot is considered a premium add-on (comparable to going from an E3 to E5 license in cost). Microsoft justifies the price by the potential productivity boost and the fact that it covers the entire suite of apps. For a large organization with thousands of users, $30/user can become quite expensive in aggregate, but Microsoft’s stance is that if Copilot truly saves each user many hours, it “pays for itself.” One nuance: the $30/user pricing applies to Copilot for Microsoft 365. Microsoft also has a free tier simply called “Microsoft Copilot,” but that refers to the basic Bing Chat-based assistant which doesn’t connect to your internal data. The enterprise Copilot is the one with full internal data access and security. Microsoft doesn’t have different pricing tiers for different features; it’s a flat add-on, which simplifies procurement. The total cost of ownership for Copilot includes ensuring you have the necessary Microsoft 365 license level and possibly training users to make use of it. If your company already invests heavily in Microsoft 365, adding Copilot’s cost might be acceptable, but it is essentially doubling the cost per user of a typical Office subscription. It’s also “all or nothing”: you get all Copilot features for that price, which is good if you will use them broadly, but if you only wanted, say, an AI search without all the document generation features, you’re still paying the full price.

Google Workspace Duet AI’s pricing was announced to mirror Microsoft’s: $30 per user per month for enterprise customers. This grants access to the AI features across Gmail, Docs, Slides, etc. In Google’s case, this is an add-on to Workspace enterprise subscriptions. So similarly, it’s a significant extra cost on top of your Google licenses. Google has hinted at tailored pricing for smaller businesses in the future, but for now the target is large enterprises (the $30/user price point clearly aligns with Microsoft’s strategy). For Google’s AI search (Agentspace), because it’s still in preview, pricing hasn’t been fully disclosed; it might become an included feature or a separate Google Cloud offering. If it follows the Duet model, one could expect it might be bundled or charged per user as well. In terms of TCO, Google’s AI would require your organization to be on Google’s platform (or at least to purchase Workspace licenses for those who need AI). Many companies either standardize on Microsoft or Google for productivity suites; few pay for both widely. So, choosing Google’s AI usually implies you’re already a Google Workspace customer. In that sense, the cost trade-off is similar to Microsoft: pay a premium to supercharge the tools you already use daily. If comparing to Rovo or Glean, the calculus might be: use Rovo or Glean as a cross-platform solution vs. pay Google for AI but perhaps get less coverage of non-Google content. For organizations that have both Atlassian and Google, an interesting note is that Rovo might actually integrate Google Drive/Docs at no extra cost, whereas Google’s own AI for those could be $30/user. The bottom line: pricing is a moving target in this space, but right now Rovo (bundled) comes out as potentially the most cost-efficient for Atlassian customers, whereas Glean, Microsoft Copilot, and Google Duet each carry substantial per-user fees in the $30+ range.

Choosing the Right Solution (When to Use Rovo vs Alternatives)

Every organization’s needs are different. Here are some considerations to determine which solution might be the best fit:

• Choose Atlassian Rovo if… your teams already use Atlassian tools extensively (Confluence, Jira, etc.) or if you want a single AI solution that unifies knowledge across many apps in one place. Rovo is ideal when you have a mix of Atlassian and other SaaS data and need to break down silos. It excels in scenarios where cross-tool context is important: for example, a project manager can query Rovo and find answers from Jira tickets, Confluence pages, Slack conversations, and Google Docs all at once. Rovo is also a great choice if you value custom AI workflows (no-code agents that non-developers can create) and if cost is a concern; Rovo’s inclusion in Atlassian plans makes it very cost-effective. However, keep in mind Rovo is cloud-only, so it fits organizations already comfortable with Atlassian’s cloud platform and data residing there. In summary, choose Rovo to empower knowledge discovery across diverse tools, especially in an Atlassian-centric environment, and when you want AI help not just in finding info but also in taking action on that info within your workflow.

• Choose Glean if… you are dealing with a very heterogeneous application landscape and you need a top-notch dedicated enterprise search solution with broad connectors, regardless of vendor ecosystems. Glean can be a strong choice for companies that might not be fully on Microsoft or Atlassian, or that have dozens of specialized systems and want an independent “single source of truth” search. Glean’s personalized results and summaries can benefit organizations where employees spend too much time searching for information buried in various tools. It’s also worth considering if your organization is willing to invest in a premium solution for knowledge management; perhaps you have experienced the pain of employees not finding answers and you attribute significant productivity loss to that. Just be prepared to justify the higher price; Glean is best when the value of faster, smarter search outweighs the cost. It might also appeal if you want an AI layer but are cautious about vendor lock-in; since Glean is not tied to Microsoft, Google, or Atlassian, it remains relatively neutral. Choose Glean for a best-of-breed search experience when budget is available and broad integration is a must, and you possibly don’t need the process automation aspects that Rovo offers.

• Choose Microsoft 365 Copilot if… your organization lives and breathes in Microsoft 365. If the majority of your knowledge and daily work is in Outlook, Teams, SharePoint, Word/Excel/PowerPoint, etc., Copilot will seamlessly amplify that environment. It’s practically a no-brainer for companies that have already bought into Microsoft’s E5 security and productivity stack and are looking to boost productivity further. Scenarios where Copilot shines include drafting and editing content in Office apps, summarizing long email threads or Teams chat discussions, and analyzing data quickly in Excel, all by just asking the AI. Copilot is also the safest bet for organizations that are very sensitive about data leaving the tenant; since it all stays within Microsoft’s cloud, you have a clear line of sight on data flow. That said, Copilot is not the best at cross-platform knowledge if you heavily use non-Microsoft tools. Copilot also comes at a high cost per user, so it’s best when you plan to roll it out to users who will truly leverage the full breadth of its capabilities. In short, choose Copilot to augment the Microsoft 365 experience: it will make your Office apps smarter and your Microsoft-stored knowledge more accessible via natural language, which can be transformative if that’s where your knowledge resides.

• Choose Google Workspace’s AI (Duet and related) if… your organization is centered on Google Workspace for email, documents, and collaboration. Duet AI is a strong choice for companies that rely on Google Docs/Sheets/Slides for content creation and want AI to help generate content or automate tasks in those apps. For instance, a marketing team that works in Google Docs might use Duet to draft campaign copy; a sales team could have Duet create slide presentations; support teams could summarize meeting recordings from Google Meet. If your data is primarily in Google Drive and Gmail, Google’s AI will have immediate context to draw on. Additionally, if you trust Google’s technology leadership in AI, you might choose their solution expecting rapid innovation. For enterprise search specifically, if you’re a Google Cloud customer, you might anticipate Google’s Agentspace maturing into a powerful offering, especially if you already use Google Cloud for other services and can integrate it. In terms of cost, similar to Microsoft, deploying Google’s AI broadly will incur significant license fees, so it’s best justified when users can take advantage of its multiple features. You would pick Google over others if you have minimal Microsoft footprint and want to avoid third-party vendors like Glean; basically, if Google is your main ecosystem, sticking with their AI keeps things simpler. One more angle: Google is continuously improving search; organizations that have very search-intensive use cases might lean on Google’s prowess there. Choose Google’s Workspace AI to supercharge Google-native workflows with AI, and keep an eye on their evolving enterprise search capabilities if you plan to extend beyond the Google world.

In many cases, organizations will use a combination of these tools. It’s not uncommon to enable Microsoft Copilot for productivity and also use Atlassian Rovo for technical teams, for example. But if you are looking to standardize on one AI knowledge assistant, consider where your company’s knowledge lives and which platform aligns best with your strategic tech stack. Rovo’s differentiated value is in tying together multiple systems through Atlassian’s lens, while Copilot and Duet excel when kept in their “home” ecosystems, and Glean offers an independent route at a premium.

No matter which you choose, it’s clear that AI-powered enterprise search and assistance is poised to significantly improve how we find and use information at work. The decision comes down to fit: the right solution should feel like a natural extension of how your teams already work, enhancing productivity without compromising security or budget.