Atlassian Rovo is a strong fit when your world already lives in Jira, Confluence, and Jira Service Management, and you want AI that works natively across the Atlassian graph.
Many IT and Head of IT buyers asking for a Rovo alternative mean something different. They want an AI agent layer on top of JSM that resolves employee requests in Slack and Teams, keeps working on Data Center, and stays focused on closing tickets rather than company wide teamwork AI.
That is the job Gaspar AI is built for.
Gaspar AI is a Rovo alternative for IT service management teams that want specialized agents on their existing Atlassian stack, focused on L1 resolution and workflows. Admins can also see which LLM powered each response, so AI and security teams can audit and govern the model behind answers.
Talk to us about Gaspar on JSM
Who this page is for
- Heads of IT / CTOs on Jira Service Management evaluating Rovo versus a third party agent layer
- Data Center customers who need AI helpdesk automation without an Atlassian Cloud only dependency
- Buyers who want chat native resolution in Slack and Teams, with tickets on JSM
- Teams that care about model transparency (which LLM answered) alongside deflection and workflow automation
- Buyers comparing "Rovo alternatives" and getting enterprise search tools (Glean, Copilot) that do not close tickets
What is new in Rovo (as of late Sep 2026)
| When | What shipped | Why it matters for this page |
|---|---|---|
| May 2026 (Team '26) | Rovo Studio GA; Max mode (early access); Teamwork Graph MCP + CLI; stronger agent governance | Rovo is a full agent building platform inside Atlassian, not "just search" |
| Jul 28, 2026 | Long Horizon reasoning in Rovo Chat (single loop, multi tool, visible traces; Claude Opus class models; MCP) | Cross product Q&A and multi step actions inside the Atlassian graph got materially better |
| Aug 18, 2026 | Code Context (open beta) for multi repo understanding via Teamwork Graph | Strengthens Rovo for engineering workflows, orthogonal to ITSM L1 |
| Aug 26, 2026 | Rovo in Microsoft 365 Copilot and Teams; natural language @Jira in Teams | Rovo now shows up in Teams for Atlassian context and ticket actions. Compete on resolution, not presence |
| Sep 1, 2026 | Studio Templates (agents + automations gallery) | Faster time to agent inside Atlassian |
| Ongoing | Rovo on Standard / Premium / Enterprise Cloud for eligible sites | "Rovo is not on Standard" is outdated for Cloud. Better angles: depth of ITSM resolution, Data Center, and model transparency |
Packaging facts (Atlassian public licensing):
- Rovo (Search, Chat, Studio, agents) is available on Standard, Premium, or Enterprise Cloud for eligible Jira / Confluence / JSM / collections once rolled out.
- Full AI experience still needs Cloud. Data Center gets connectors into Cloud AI, not a full DC native Rovo stack.
Rovo vs Gaspar AI at a glance
| Atlassian Rovo | Gaspar AI | |
|---|---|---|
| Best when | Work and knowledge already center on Atlassian Cloud + Teamwork Graph | You need an AI helpdesk layer in Slack/Teams on top of JSM |
| Where employees ask | Atlassian surfaces, plus connected apps (incl. Teams/Copilot for Atlassian context) | Slack and Microsoft Teams (with tickets on Jira Service Management) |
| LLM transparency | Primarily Atlassian managed models inside Rovo | Admins can see which LLM powered each response |
| Deployment | Cloud first (DC knowledge via connectors; full AI still Cloud) | Cloud, Data Center, or your own infrastructure |
| Core job | Search, chat, Studio agents, and actions across the Atlassian graph | Resolve L1 issues, automate workflows, route tickets, approvals |
| Knowledge | Deep Atlassian graph + connectors (+ Code Context for repos) | Confluence plus other KM sources (e.g. SharePoint, Google Docs, Notion, Coda) |
| Automations | Rovo Studio agents / templates / automations inside Atlassian | No code workflows, out of the box automations, multi app actions |
| Commercial fit | Included with eligible Cloud plans | Automation across Free through Enterprise Atlassian plans with no usage limits |
Keep Rovo when native Atlassian search, Studio agents, and graph context are enough. Add Gaspar when deflection, chat native fulfillment, Data Center, and LLM transparency are the buying criteria.
What "best alternative for Rovo AI" usually means (and why lists miss ITSM)
Independent "Rovo alternatives" roundups often name eesel, Risotto, or Glean (plus Microsoft 365 Copilot, Notion AI, ChatGPT). Search and general AI assistants answer a knowledge question. They rarely close JSM tickets the way an ITSM agent layer does.
IT buyers asking Heads of IT questions usually want:
- Auto resolve common employee requests
- Ticket create / smart route when the bot cannot finish
- Approvals and workflows in Slack or Teams
- Something that works with the JSM they already run, including Data Center
- Clear visibility into which model produced each answer
Gaspar AI is aimed at that list: an ITSM agent layer, not a company wide search suite.
Why teams pick Gaspar instead of (or beside) Rovo
1. Visibility into the LLM behind each response
With Gaspar, admins can see which LLM powered each response. That matters for AI governance, security reviews, and regulated buyers who will not accept a black box helpdesk agent. Rovo runs primarily on Atlassian managed models inside their stack. Gaspar makes the model choice auditable per interaction.
2. Cloud and Data Center
Gaspar integrates whether you host Atlassian in the cloud or on Data Center / your own infrastructure. Rovo's full AI path remains Cloud centric. DC customers still need a Cloud subscription to maximize Rovo. That is a hard requirement for many regulated buyers.
3. Employees stay in Slack and Teams
Gaspar runs as a generative AI virtual agent on Slack and Microsoft Teams, creating and routing tickets on Jira Service Management when needed. Rovo's Teams/Copilot presence is real, and it is optimized for Atlassian graph answers and @Jira actions. Gaspar's job is still closing the request (reset, provision, approve, route), not only filing or explaining it.
4. Resolution, not only answers
Gaspar is built to resolve repetitive issues (password resets, provisioning, group management, and similar L1 work), create tickets when needed, and hand off with context. Public positioning: automatic resolution of more than 40% of employee issues without human intervention on Slack and Teams.
5. Knowledge beyond Confluence alone
Beyond Confluence, Gaspar connects to other knowledge systems teams already use (SharePoint, Google Docs, Notion, Coda, and more) so answers are not trapped in one wiki.
6. No code automation and Admin Hub
Out of the box automations, approvals in chat, ticket automation and smart routing, plus an Admin Hub with analytics and AI recommendations for missing knowledge and high impact automations.
7. Predictable ITSM automation cost
Gaspar positions automation across Free, Standard, Premium, and Enterprise with no usage limits, so L1 deflection does not depend on competing for org wide AI quota inside Atlassian.
When to keep Rovo, when to choose Gaspar, when to use both
Keep / start with Rovo if:
- You are on an eligible Atlassian Cloud plan and the main job is search + agents across Jira + Confluence (+ Teamwork Graph)
- Studio / Long Horizon / Max style multi step work inside Atlassian is the priority
- One vendor and one bill matter more than chat native multi system fulfillment
Choose Gaspar if:
- You are on Data Center (or hybrid) and still need serious AI deflection
- Head of IT / CTO cares about ticket volume, L1 auto resolve, and LLM transparency
- Slack/Teams is where employees ask for help, and you need fulfillment, not only answers /
@Jira - You want an AI layer on JSM without rip and replace
Use both if:
- Rovo covers Atlassian native search, incident context, and Studio agents
- Gaspar owns front line employee support and cross app fulfillment on Slack/Teams, with tickets on JSM
FAQ
What is the best Rovo AI alternative for Jira Service Management?
Gaspar AI is a strong Rovo alternative for ITSM teams that want specialized agents on Slack and Microsoft Teams on top of Jira Service Management, especially when Data Center, L1 resolution, or LLM transparency matter.
Is Gaspar AI a replacement for Rovo?
It can be an alternative or a complement. Replace Rovo when you need a helpdesk agent layer and deployment flexibility. Keep Rovo for Atlassian native search and Studio agents, and add Gaspar for chat native resolution.
Does Rovo work on Jira Service Management Standard?
Yes on Cloud Standard (and higher) for eligible sites. Gaspar remains the alternative when you need ITSM resolution on Data Center, chat native fulfillment in Slack/Teams, or auditable LLM choice per response.
Does Gaspar AI support Atlassian Data Center?
Yes. Gaspar integrates with Atlassian products whether you run Cloud, Data Center, or other infrastructure.
Does Gaspar show which LLM is used?
Yes. Admins can see which LLM powered each response, so teams can audit and govern the model behind answers.
How is Gaspar different from Glean or Copilot as a "Rovo alternative"?
Glean and Copilot are usually compared as enterprise search / productivity assistants. Gaspar is an AI helpdesk and specialized agent layer for ITSM workflows on top of tools like JSM, Freshservice, and ServiceNow. (Rovo in Microsoft 365 Copilot is Atlassian context inside Copilot, still not a dedicated L1 fulfillment layer.)
Will Rovo's Long Horizon / Studio make Gaspar unnecessary?
They make Rovo stronger at multi step work inside the Atlassian graph. They do not remove the need for a dedicated ITSM agent layer that lives in Slack/Teams, resolves L1, runs on Data Center, and makes the LLM behind each response auditable.