Jellyfish really helps me understand where my teams are working and how effective our roll out of AI has been.

I use Jellyfish for tracking engineering metrics like sprint reviews and throughput. I appreciate the customer service, especially Andrey, who is quick to respond and help. I like the UI of the platform as well. It saves me time going through Jira and building manual views because Jellyfish consolidates and standardizes the information well.

I like the ability of Jellyfish to tie into the current tools we're using across our SDLC, like Jira and GitHub, and bring them together. It's great for understanding our kind of overall development productivity across teams and measuring it at various levels like group and org level. What stands out for me is how it can assess what's actually happening and how we deliver product or value back to our customers. The integration helps us tie metrics from different platforms, like linking a Jira ticket to a GitHub pull request and tying that to an Azure pipeline run. This brings a lot of value across the SDLC as it's crucial to see the bigger picture, not just isolated metrics. I also think the AI impact feature has been a starting point that gets my team and organization thinking differently in the era of AI.