There are now numerous ways to build custom AI Agents. But which is right for your developer skills and use case?
In today’s article, we’re comparing two key players in the agentic AI space: Amazon Web Services (AWS) Strands and Atlassian’s Rovo Studio.
Let’s begin.
ℹ️ Spotlight on AWS Strands and Rovo Studio
What is AWS Strands?
AWS Strands is an open-source Software Developer Kit (SDK), which enables teams to build agentic AI capabilities in Python or TypeScript, as part of their code-flow.
AWS Strands agents can integrate with numerous third-party platforms and tooling.
What is Atlassian Rovo Studio?
Rovo Studio, meanwhile, enables teams to create custom AI Agents using natural language prompts, within the Atlassian Cloud Platform.
Rovo Agents are primarily used in Atlassian apps (such as Jira, Jira Service Management and Confluence), but can integrate with other tools using third-party MCP (Model Context Protocol) servers.
AWS Strands vs Atlassian Rovo Studio: What’s the difference?
The primary difference between AWS Strands and Rovo Studio is that AWS Strands is platform-agnostic, whereas Rovo Studio is native to the Atlassian Cloud Platform (although custom Rovo Agents can integrate with other tools).
Another notable difference is the programming language for each option. You’ll need to know Python or TypeScript to build an AI Agent in AWS Strands, whereas Studio is a low-code platform, meaning you can create your AI Agent using natural language prompts.
Ostensibly, this means that AWS Strands is a better fit for Software Development and Engineering teams with strong programming skills, and Rovo Studio is a great option for citizen developers and business teams.
The reality, however, is a little more nuanced.
Seeking agentic AI inspiration? Browse our library of custom AI Agent use cases, to understand how organisations are deploying agentic AI in the real world.
AWS Strands vs Atlassian Rovo Studio: What’s the best fit for you?
Let’s start with your use cases. If you’re using Atlassian apps, like Jira or JSM, and want to automate manual or repetitive tasks, Rovo Studio is probably a good bet. You can create and deploy agentic AI to drive simple workflows, enhance efficiency and streamline processes.
But what if you’re looking for something more multi-faceted? Well, if you want to stay in the Atlassian ecosystem, there is another option. Atlassian Forge enables you to build custom Rovo Agents using Javascript, so you can tackle more complex use cases.
Comparing Rovo Studio vs Forge? Take a read of our comparison guide!
If you’re not working exclusively with Atlassian solutions, and want to create agentic AI as part of your code flow, AWS Strands is a strong option.
This is particularly true if you need to build multi-agent systems, or integrate a range of different platforms, as it tends to be easier to manipulate and pull data in with AWS Strands, when compared to low or no-code solutions such as Rovo.
For tooling-agnostic and potentially complex use cases, we’d recommend exploring AWS Strands – particularly if you have in-house development skill.
Do you want to realise value from your AI Agents faster? Our Rovo AI Accelerator could be just what you need – designed to help teams embed and deploy Rovo for long-term success.
AWS Strands vs Atlassian Rovo Studio at a glance
Let’s summarise the key similarities, differences and use cases for AWS Strands vs Rovo Studio, to help inform your decision around which platform is right for you.
| Category | Rovo Studio | AWS Strands Agents SDK |
|---|---|---|
| Ease of use | High. Natural language. No-code friendly | Moderate. Requires coding and knowledge of Python or TypeScript |
| Target users | Business teams, Atlassian admins | Software developers, ML engineers |
| Primary language | Natural language prompts (Note: JavaScript is used in Atlassian Forge) | Python |
| Agent creation | Describe Agent using Rovo Chat function (natural language) | Define model, prompt and refine tools in code |
| Tooling model | Prebuilt integrations + automation rules + app builder | "Toolbelt" concept—plug APIs/functions as tools |
| Integrations | Deep Atlassian ecosystem (Jira, Confluence, etc.) + some third-party apps | AWS-native (Bedrock, Lambda, etc.) + external APIs + multi-model providers |
| Customization level | Medium. Guided and constrained by Atlassian Cloud Platform | High. Full control over logic, architecture and orchestration |
| Use cases | Workflow automation, knowledge assistants, support agents, internal productivity | Autonomous agents, multi-step reasoning systems, backend automation, complex pipelines |
| Deployment | SaaS (inside Atlassian Cloud) | Flexible: Local, Cloud, Microservices, AWS infrastructure |
| Pricing model | Included in Atlassian Cloud plans | Open-source SDK |
| Vendor lock-in | High (Atlassian ecosystem) | Low–moderate (AWS ecosystem optional) |
| Multi-model support | No | Yes |
| Best for | Business teams automating work | Engineering teams building custom AI systems |
AWS Strands vs Atlassian Rovo Studio at a glance
Hopefully by now you feel you’ve got a good handle on the comparison between AWS Strands and Rovo Studio – and understand which platform is right for your agentic AI needs.
We’ll leave you with this. Always be led by your use case, rather than trying to create something and then bend it to fit your needs. The joy of custom AI Agents is that you can build entirely bespoke solutions to meet your teams’ exact needs – so don’t compromise that with an il-matched platform.
Consider your tooling (Atlassian or other), level of developer skill, and complexity of use case – and then decide whether AWS Strands, Rovo Studio or even Forge might be best suited for you.
And if you need support bringing your agentic AI to life, why not turn to us? As an Atlassian Platinum Solution Partner, AWS Select Partner, and with a team of AI specialists on board, we’re a safe pair of hands for enhancing your end-to-end processes with powerful, responsible embedded AI.
