The big idea behind AI is pretty simple: let the bots handle the repetitive grunt work so your team can focus on what people do best. In a perfect world, AI agents would be like extra teammates who work 24/7, connecting all your different apps and smoothing out your workflows. Atlassian is chasing this vision with Rovo agents, their in-house AI for teamwork inside their massive ecosystem.
But as teams start using them, they’re finding it’s not quite that simple. While Rovo agents are powerful inside their home turf, they come with some real headaches around cost, complexity, and what they can connect to. It’s become such a sticking point that some analysts have noted companies are struggling to justify the cost, leading Atlassian to change its pricing by bundling Rovo into its most expensive subscription plans.
In this guide, we’ll break down what Rovo agents are all about for 2025. We’ll look at their main features, how you can use them, and the hidden limits you should know about. We’ll also explore why many teams are searching for more flexible tools that can work across all their apps, not just one.
What are Rovo agents?
Simply put, Rovo agents are AI-powered teammates you can set up to work alongside you, cut down on manual tasks, and take action for you right inside the Atlassian suite. Think of them as specialists you can call on in Jira, Confluence, and other Atlassian tools to help get work done.
To get a feel for what they do, it helps to know the three main flavors they come in:
- Out-of-the-box agents: These are the ready-made agents from Atlassian for everyday tasks. You can use them straight away to summarize a document, translate text, or help clean up your Jira backlog with zero setup.
- Custom agents: If you have a very specific process, you can build your own agent with a tool called Rovo Studio. This lets you give an agent a unique job, connect it to certain knowledge sources, and tell it exactly what to do.
- Marketplace agents: These are agents made by other developers to help Rovo work with other apps. For instance, the team behind the Budgety for Jira app built an agent so users could ask for financial data through Rovo’s chat.
Core features and use cases of Rovo agents
Before we get into the downsides, let’s look at what Rovo agents were built to do well. For teams that live and breathe Atlassian, they offer some pretty neat ways to automate work.
Automating tasks within Jira and Confluence with Rovo agents
The biggest selling point for Rovo agents is how deeply they connect with Jira Service Management and Confluence. You can ask an agent to do things that would normally take up a chunk of your time.
For example, you could create an agent to groom your Jira backlog by finding any issue that hasn’t been touched in 90 days and flagging it for a review. Or you could have an agent whip up a weekly project summary on a Confluence page, pulling updates and key stats from your project boards automatically. It keeps everyone on the same page without anyone having to manually put the report together.
How Rovo agents source knowledge from connected apps
Atlassian is aware that a company’s brain isn’t just stored in its products. Rovo agents can connect to outside knowledge sources like Google Docs and Microsoft SharePoint to find information when you ask a question. This helps an agent give a fuller picture by searching both your Confluence space and your shared drive. It’s a good feature, but its main purpose is to pull information into the Atlassian world, not to take action in other tools.
Building custom workflows for Rovo agents with Rovo Studio
For teams with their own way of doing things, Rovo Studio is where you can build custom agents from scratch. It gives you a place to define what you want the agent to do, which documents it should read, and what actions it’s allowed to take. This level of control is great for building an agent that fits your team’s process perfectly. But as we’re about to see, that power comes with a pretty steep learning curve.
The hidden challenges and limitations of Rovo agents
While Rovo agents look good on paper, many teams are finding they come with some serious trade-offs that get in the way of automating work from start to finish.
The "walled garden" problem for Rovo agents: limited cross-platform integration
Rovo’s biggest strength is also its greatest weakness: it’s made for Atlassian first and foremost. While it can connect to some outside tools, its ability to actually do anything is mostly stuck within Jira and Confluence. This creates a "walled garden" that can be a major headache for teams who use a mix of different, specialized tools to get their work done.
Let’s say you need an AI agent to reply to a customer ticket in Zendesk, summarize the key points of a conversation in Slack, and then go update a customer’s record. Rovo just isn’t built for that. It can read some outside information, but it can’t operate inside other platforms. In contrast, tools like eesel AI are designed to be a flexible layer that works across all your apps, letting you automate workflows wherever they happen.
Navigating the complex and unpredictable pricing model for Rovo agents
Rovo used to have its own price tag, but Atlassian has since rolled it into its high-end Premium and Enterprise plans. This means that to get Rovo agents, you have to upgrade your entire Atlassian subscription, which can be a huge cost that many teams just can’t swallow.
On top of that, Rovo’s pricing includes confusing quotas for "Objects" (an indexed item, like a single Google Doc) and "Requests" (any interaction with an agent). According to their own docs, a team of 200 users gets 300,000 objects and 50,000 requests per month. While Atlassian says they aren’t charging for overages right now, they’re tracking them, which is a pretty clear sign that extra fees are coming. This makes it almost impossible to predict your costs and show a clear return on your investment.
This is a world away from simpler models. For example, eesel AI offers predictable, flat-rate pricing based on how many AI interactions you use, not how many people are on your team. This helps keep costs from ballooning as your company gets bigger.
The steep learning curve and "blank canvas" factor for Rovo agents
Getting a custom Rovo agent to do what you want reliably is harder than it sounds. As people have shared in blogs like this one from Eficode, it takes a lot of trial-and-error and very specific "prompt engineering" to get it right. This can be a massive time-waster, especially for teams without a technical background who just want something that works.
Even Atlassian’s Head of AI Product, Jamil Valliani, admitted this was an issue in the TechTarget article, saying that the "blank canvas… can be really intimidating" for people. Teams need a tool that helps them find a solution, not one that gives them a blank screen and expects them to suddenly become AI experts.
| Feature | Atlassian Rovo | eesel AI |
|---|---|---|
| Pricing Model | Per-user, bundled in high-tier plans | Flat-rate, based on interactions |
| Usage Limits | Quotas on "Objects" & "Requests" | Generous interaction allowance |
| Cost Predictability | Low (tied to users & future overages) | High (predictable monthly cost) |
| ROI | Difficult to calculate per-user | Clear, based on automated interactions |
A more flexible alternative to Rovo agents for true cross-platform automation
The walls around Rovo have led many teams to look for AI solutions that are more flexible, affordable, and easier to use. eesel AI was created to solve these exact problems by acting as a smart automation layer that works with the tools you already have.
Break free from the ecosystem with over 100 integrations
Unlike Rovo, eesel AI isn’t trying to pull you into a single ecosystem. It’s designed to sit on top of your current software stack, with over 100 one-click integrations that connect to the platforms where your team is actually working. And it goes way beyond just connecting to document folders.
You can connect eesel AI to your help desks, and even e-commerce platforms like Shopify. This means you can build workflows that handle tasks across your entire company, not just inside one product.
Get predictable ROI with pricing that actually makes sense
The pricing model for eesel AI is simple and transparent. Instead of making you pay for every single user, eesel AI’s plans are based on the number of monthly AI interactions (like an AI-powered reply or action). This means you only pay for the value you’re actually getting. It’s a model that grows with your usage, not your employee count, which is a breath of fresh air for growing teams. You can add new people or whole departments without getting a surprise on your next bill.
Go from idea to a working bot much faster
To fix the "blank canvas" problem, eesel AI gives you a guided, easy-to-follow setup that lets anyone build a powerful AI agent. Here are a few features that make it so much simpler:
- Simulation: Before you let your agent loose, you can test it on your past data. This lets you see exactly how it would have performed, check its accuracy, estimate your cost savings, and find any gaps in its knowledge before it talks to a single real user.
- Natural Language Configuration: You don’t need to be a prompt wizard to set up your agent. You can tell it what tone to use, when to escalate an issue to a human, and what rules to follow using plain English.
- Multi-Bot Architecture: A single eesel AI account can run multiple, specialized bots. This means you can have one bot for your Support team, another for IT, and a third for HR, and each one can have its own separate knowledge sources and permissions.
Rovo agents vs. eesel AI: a head-to-head comparison
So, how do they stack up? Here’s a quick rundown.
| Capability | Rovo Agents | eesel AI |
|---|---|---|
| Primary Use Case | Automation within the Atlassian suite | Cross-platform automation (support, IT, internal) |
| Integrations | Atlassian-centric, ~50 connectors | 100+ across help desks, chat, docs & more |
| Setup & Configuration | Rovo Studio, requires prompt engineering | Natural language prompts & simulation |
| Pricing Model | Per-user, bundled with high-tier plans | Flat-rate, based on interaction volume |
| Best For | Teams deeply embedded in Jira/Confluence | Teams needing flexibility and broad tool support |
Conclusion: Are Rovo agents the right AI agent for your team?
So, what’s the final verdict? Rovo agents can be a decent choice for teams whose work happens almost entirely inside the Atlassian bubble and who are already on (or don’t mind paying for) a Premium or Enterprise plan. The deep connections with Jira and Confluence can definitely help streamline work for those teams.
But for most modern companies that use a mix of different tools, Rovo’s limits become obvious pretty quickly. The walled-garden design, confusing and expensive pricing, and steep learning curve are major roadblocks to automating work across the entire business.
The need for clear pricing, broad integrations, and tools that are just plain easier to use is why so many businesses are looking for more flexible options. eesel AI was built from the ground up to be a powerful, scalable, and easy-to-use AI automation layer that works with the tools you’re already using, freeing you to build smarter workflows without compromise.
Ready to automate workflows without limits?
If you feel boxed in by your current tools, it’s time to see what a truly cross-platform solution can do for you.
See how eesel AI connects with all your tools and provides predictable ROI.
Or, try it for free and see how you can build a powerful AI agent in just a few minutes.
Frequently asked questions
Rovo agents don’t have a standalone price. They are bundled into Atlassian’s high-tier Premium and Enterprise subscription plans, so your entire organization must upgrade to get access, making it a significant investment.
While they can read data from some external sources like Google Docs, their ability to perform actions is almost entirely limited to the Atlassian ecosystem. They cannot automate tasks inside other apps like Slack or Zendesk.
Building custom agents using Rovo Studio has a steep learning curve and often requires significant trial-and-error with prompt engineering. This can be challenging and time-consuming for non-technical teams.
Probably not. Rovo agents are designed for teams whose work lives almost entirely within Atlassian products. If your workflows rely on a mix of different tools, you will likely find their “walled garden” approach very limiting.
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