Hello,
We are currently evaluating Atlassian Rovo as part of our Data Center to Cloud migration. We are concerned about the sustainability of the usage-based credit model at an enterprise scale. Atlassian has been been pushing moving to cloud to use Rovo everywhere but here are some examples that are very limited.
We have currenctly 31500 credits for 15k users
Automation with rovo can bust your credit quickly
- An automation rovo to automatea component and labels selection with custom agent in test for 1 day with 1 person took 3000 credits already
| | |
|---|
Basic | Add label on issue creation | 0 |
Simple | Extract keywords from summary and add as labels | 10 |
Deep | Generate root cause analysis from all fields and attachments | 100 |
250000 credit just for one automation
- Credit by execution : 10
- Total credits/month: 25000 (execution conservative for us, more on data center currently) x 10 = 250,000 credits
Deep searches are totally unusable on big sites
- Example : calculate a number field by platform field, 100 issues take about 10 minutes, 1000 issues never finish. Our needs are easily more than 10k+.
Other AI does not charge for internal product simple chat
We have Microsoft copilot enterprise has no credit limit on internal microsoft app for chat with where rovo use credit for everything even their own app. https://learn.microsoft.com/en-us/microsoft-copilot-studio/requirements-messages-management
In conclusion, we are not sure if pushing Rovo internally will be solution for us, since there's no clear direction on how we can stop the usage of Rovo on a site, an automation, or simple chat by users that can directly bust your montly credit for the whole enterprise in basicly 5 minutes.
Martin Poirier
Ubisoft