What I like best about Jellyfish is its ability to bring engineering data together in one place and turn it into meaningful, actionable insights. The visibility into engineering capacity, investment allocation, delivery performance, and team productivity makes it easier for Product and Engineering leaders to make informed decisions. I also appreciate the ability to drill down from high-level executive metrics to team-level details, identify bottlenecks, and have data-driven conversations around continuous improvement and business outcomes. Review collected by and hosted on G2.com.

While Jellyfish provides valuable insights, there are opportunities to improve the user experience. Some dashboards and reports could be more intuitive and easier to customize, particularly when trying to get specific views for different leadership audiences. At times, interpreting metrics requires additional context to ensure they are not viewed in isolation. I would also like to see more flexibility in reporting, easier drill-down capabilities, and stronger integration with Product metrics to better connect engineering activity with customer and business outcomes. Review collected by and hosted on G2.com.

Insights on PR Cycle time, Issue cycles time, CapX, and Team performance in general are my favorite features I use on a regular basis. I love the MCP so I incorporate this data into my own reporting and presentations. Review collected by and hosted on G2.com.

I wish I had QA cycle aspects involved, since some of it is QA engineering and it would be nice to have KPIs here. Review collected by and hosted on G2.com.

As I have used Jellyfish more, I have found its biggest value is not just the visibility it provides, but how it supports better planning and leadership conversations. It brings engineering delivery, team allocation, capacity, and investment priorities into one place by connecting data from tools such as Jira and GitHub.

The dashboards make it easier to identify delivery risks, understand where teams are spending their time, and discuss trade-offs without manually consolidating information from multiple sources. It is especially useful for creating a shared view between engineering, product, PMO, and leadership teams. Review collected by and hosted on G2.com.

The initial setup and learning curve could still be improved. Configuring teams, investment categories, and metrics may require support from experienced users or the PMO team.

More guided onboarding, clearer explanations of how metrics are calculated, and easier report customization would help users become productive more quickly. It would also be useful to have more flexibility when tailoring dashboards and reports for different audiences. Review collected by and hosted on G2.com.

I really like the interface and how easy it is to navigate through the data. If you have your hierarchy set up and use Jira effectively, the integration lets you move up and down through the different levels of your organization and see how data from smaller units rolls up into the larger picture. Review collected by and hosted on G2.com.

There was a bit of a learning curve at first as I got used to the navigation, but once I understood where to find the information I needed, I could use favorites, bookmarks, and stars to quickly access the information I rely on regularly. Review collected by and hosted on G2.com.

The AI insights built within the product takes the heavy lifting of evaluating the data off of the user. The UI is fairly straightforward with pleasing visuals throughout the product. Pulling data from our disparate systems and present a full picture across our engineering organization in one place is a big win. When I do have to deal with the support team, they have been prompt and helpful in resolving my issues. Review collected by and hosted on G2.com.

The biggest issue I have with Jellyfish is how it attributes work done by engineers as AI assisted work. It's really making a guess based on if there are AI signals the day that they do a PR which isn't really a great determination in my opinion. Not having the ability to designate static teams has also been a problem when we have teams that are support teams who's work spans multiple JIRA projects. Review collected by and hosted on G2.com.

The effort-based allocation model is the standout. Jellyfish translates raw development activity into an FTE-equivalent split across investment categories (Growth, KTLO, Support) based on actual effort signals rather than ticket counts — which is critical, because counting issues badly misrepresents real work. This is what made my monthly CEO and board reporting credible: leadership could trust an "X FTE went to Growth this month" figure because it reflected effort, not just Jira volume. The mapping of investment categories to our own strategy taxonomy and the month-over-month trend views also let me show direction over time with minimal manual assembly, and the delivery and AI-assisted PR metrics fed our AI-adoption reporting well. Review collected by and hosted on G2.com.

The biggest frustration is the newer AI impact reports: there's no way to export the underlying data to CSV. The reports render fine in the UI, but if you need the numbers for your own analysis — cohort breakdowns, month-over-month trends, feeding an executive deck — you're stuck. You can look at the data but you can't take it with you, so getting it into a usable format means manual extraction rather than a simple download. For a metrics platform whose whole value is helping you report, locking the data inside the dashboard defeats the purpose.

On top of that, I've seen the per-tool detail figures and their aggregate rollups diverge by around 10 percentage points, which is a real problem when the aggregate is the number going in front of the board. Both issues are workable, but they add reconciliation and extraction steps to what should be a clean pull. Review collected by and hosted on G2.com.

I use Jellyfish to understand how testing and engineering effort contribute to overall product delivery and business priorities. It helps me track where QA and automation work is going, identify bottlenecks in the development workflow, and solve the lack of visibility between testing work and broader engineering priorities. With Jellyfish, I can better connect testing activities to feature delivery, identify where delays are coming from in the pipeline, and understand how much effort is going into. I particularly like the visibility it brings across engineering teams and QA work in relation to business priorities, along with reports on demand and budget planning. The visibility and reporting feature is especially valuable, as I can see consolidated reports that show where testing efforts are concentrated, how they align with development progress, and where delays and bottlenecks occur. This makes it easier to pinpoint issues like slow handoffs between development and QA. After moving to Jellyfish, manual work has been reduced, and the process of collecting data from multiple tools has been drastically reduced. Review collected by and hosted on G2.com.

While the dashboards provide strong visibility, they can sometimes feel a bit complex or dense when trying to drill down quickly into QA-specific insights. More customisable or role-focused views would make it easier to surface what's most relevant without extra filtering. Review collected by and hosted on G2.com.

Jellyfish took a complicated, manual process we had for capitalizing software development costs and made it a breeze for us in Accounting. Our old process of using timecards & tracking epics was very burdensome, taking atleast a full day of close to compile. With Jellyfish, at the click of a button I have all the data I need to book our monthly entry. The documentation Jellyfish provide has also been extremely helpful to communicate with our auditors on our processes and how everything works. Review collected by and hosted on G2.com.

None - Jellyfish has been amazing. I really have nothing bad to say. Review collected by and hosted on G2.com.

graphs and representations good way to see progress Review collected by and hosted on G2.com.

navigation sometimes confusing, but not overall its good Review collected by and hosted on G2.com.

I like that it integrates with various data platforms (Jira, IncidentIO, Gitlab), makes sense of the data and combines the data well behind the scenes. Review collected by and hosted on G2.com.

Dashboard creation is very restricted. Even with latest custom metrics, there is still a long way to go. Review collected by and hosted on G2.com.