Jellyfish Software Engineering Intelligence Platform

What do you like best about the product?

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.

What do you dislike about the product?

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.

What problems is the product solving and how is that benefiting you?

Before I had to go to disparate systems such as JIRA, GitLab, Github, and Linear to get data to understand our engineering team's performance. Now I can go to Jellyfish to have those data and metrics aggregated under one platform to understand the teams and organization's performance.

What do you like best about the product?

Jellyfish helps me know where I stand in AI usage and lets me see the usage of my teammates as well. It's useful for understanding how much I depend on AI. I find all the features good, and the initial setup with SSO login was easy.

What do you dislike about the product?

Nothing

What problems is the product solving and how is that benefiting you?

I use Jellyfish to track AI usage, helping me understand my dependency and where I stand. It also lets me see my team's usage, which is useful.

What do you like best about the product?

the ability to quickly view my team's progress in metrics we are tracking.

What do you dislike about the product?

sometimes the interface can be clunky and dificult to navigate. I have to know where I am going to get what I need.

What problems is the product solving and how is that benefiting you?

it is giving me visibility into how my teams are performing

What do you like best about the product?

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.

What do you dislike about the product?

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.

What problems is the product solving and how is that benefiting you?

It answers the core question my leadership asks every month: where is engineering effort actually going, and is it aligned to strategy? The FTE allocation across Growth/KTLO/Support gives me a defensible, repeatable way to report that, plus the delivery and AI-assisted-development metrics I need to show whether our tooling investment is moving velocity. The benefit is a monthly executive narrative grounded in effort data rather than anecdote or raw counts.

What do you like best about the product?

Jellyfish provides insights into my PR cycle time and issue cycle time, while also allowing me to track my quarter-over-quarter growth. This helps me monitor my performance metrics effectively and present data-backed progress.The data is actually useful day-to-day, I can see where my time is going, how much is planned work vs interruptions, and where PRs are getting stuck in review. Found out 40% of my team's capacity was getting eaten by unplanned work. That's not something you notice until you see it in a chart.

What do you dislike about the product?

The dashboard is slow, and UI can be a bit better. Default benchmarks are calibrated for average eng teams — if you move fast, your metrics look "unhealthy" out of the box which is misleading.

What problems is the product solving and how is that benefiting you?

Sprint planning used to be based on gut feel and optimism. Now I have actual cycle time data, PR review lag, and capacity breakdown to reference. Our cycle time dropped from 4.5 days to 2.8 days once we identified review lag as the bottleneck and fixed it. Conversations with my manager about workload are easier too, I don't have to explain why something took long, the data tells the story.

What do you like best about the product?

The real value for me as a PM is the visibility into our engineering workflow. I can track Issue Cycle Time, PR Cycle Time, unlinked pull requests, and PR comments, all connected to Jira so there's no data silos. It shows exactly where the team is spending their time and where bottlenecks exist. No more guesswork on timelines.

What do you dislike about the product?

The UI could be cleaner, sometimes it takes extra clicks to get insights I need. Minor friction points, but they add up when you're iterating quickly. Rest the team is doing a good job.

What problems is the product solving and how is that benefiting you?

Before Jellyfish, I had no visibility into development cycle times or where the team actually spent their time. Now I can see blockers in real-time, unlinked PRs, slow issue resolution, approval delays, all connected to Jira. The team can iterate faster because bottlenecks are visible, not hidden. Bottom line: better planning, faster shipping, fewer surprises.

What do you like best about the product?

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.

What do you dislike about the product?

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.

What problems is the product solving and how is that benefiting you?

Jellyfish provides visibility into our information in a way we couldn’t get anywhere else. In particular, it shows where developers are actually spending their time, not just where they plan to spend it. The signals Jellyfish captures give us a clearer view of reality than our other planning tools. It also enables capitalization tracking without forcing us to rely on time tracking across our work.

What do you like best about the product?

The DevFinOps capabilities and DORA metrics have changed the way we operate as an engineering organization.

What do you dislike about the product?

I wish there was more in the way of ‘engaging’ users, driving them to the platform.

What problems is the product solving and how is that benefiting you?

Labor capitalization, DORA metrics, AI Impact, synthesizing Jira, Gitlab, and Cursor data.

What do you like best about the product?

I like that Jellyfish provides clear visibility into my work, eliminating the need for manual tracking. The simple dashboards make it easy to understand performance trends quickly. It's incredibly useful for identifying delays in testing or review cycles, which helps me improve consistency and maintain accountability. The setup was straightforward, with smooth integration of tools like Jira and Git, and it was easy to start using. Switching to Jellyfish from more manual tracking methods made performance tracking more structured and data-driven. I appreciate how it gives me a clear view of my work and contributions while using it alongside other tools like Git, Jira, and CI/CD pipelines.

What do you dislike about the product?

The AI insights could be more detailed and tailored to QA needs, like providing insights on test coverage gaps, identifying flaky tests, and recurring defect patterns. It would also be beneficial if the AI could suggest clear actions on where to improve tests or highlight potential risks in upcoming releases.

What problems is the product solving and how is that benefiting you?

I use Jellyfish to track my QA performance with clear dashboards, helping me quickly identify delays in testing cycles. It improves consistency and accountability by providing visibility into my time usage and contributions.

What do you like best about the product?

You can look at Team Pulse, Team Summary and Individual statistics during Retrospective for what went well, didn't go well.

What do you dislike about the product?

AI Impact was not integrated successfully with Amazon Q.

What problems is the product solving and how is that benefiting you?

The biggest advantage is categorizing where the time is being spent by the developers, i.e. we have decided categories for each epic and defect.