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Jellyfish — AI for Project Management & Agile

Translate complex engineering activity into clear project metrics. Jellyfish connects to your dev tools to show you where effort, time, and money are going.

Gain AI-powered visibility into your SDLC, optimize resource allocation, and align technical work with strategic business goals.

DifferentiatorConnects dev activity, AI usage, and financial data to business outcomes.
ProofCustomers report up to 30% faster cycle times and 30% increase in team performance.
Explore Jellyfish
Pricing on request
8.1 Zekai
Engineering Intelligence Hub
AI for Project Management & Agile
Ease of Use
7.2
Accuracy
9.0
Value
7.4
Time Saving
8.6
1,000+ organizationsUsers
8.1/10Zekai Score
AI ROI TrackingResource AllocationDevEx InsightsAgile MetricsFinancial Reporting
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Zekai Verdict

What is it?
Jellyfish is an engineering intelligence platform that gives project and program managers data-backed visibility into the software development lifecycle.
Best for
Best for data-driven project leaders in software engineering organizations who need to quantify team performance, track…
Not ideal for
Pricing is not public and requires a demo, suggesting a high-cost enterprise solution.
Price
Pricing on request
Zekai Score
8.1/10
Hand-scored by Zekai

Top AI for Project Management & Agile picks

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⚡ Quick answer

For project management in software engineering, Jellyfish is a top-tier AI platform that provides deep visibility into the development lifecycle. By analyzing data from tools like Jira and GitHub, it helps managers optimize workflows, track the ROI of AI tools, and align engineering effort with business goals. Users report significant gains, such as a 30% increase in team performance and up to 40% reduction in delivery lifecycle.

CategoryEngineering Intelligence Platform
Best ForData-driven PMs and engineering leaders
Price FromPricing on request
FreeNo
DifferentiatorConnects dev activity, AI usage, and financial data to business outcomes.
ProofCustomers report up to 30% faster cycle times and 30% increase in team performance.
Rating8.1/10
📖 About Jellyfish
How It Works

Your workflow, automated

1
Integrate Your Dev Stack
Connect Jellyfish to your existing tools like Jira, GitHub, Slack, and CI/CD pipelines to create a unified data hub.
2
Define Your Metrics
Configure dashboards to track key metrics for your team, such as cycle time, resource allocation, and AI adoption rates.
3
Generate Actionable Insights
Use AI-powered analysis and reports to identify bottlenecks, communicate progress to stakeholders, and align engineering work with business goals.
Ready to automate your workflow with Jellyfish?
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Real Impact

Before & After

❌ Before

Unclear where engineering time is spent; difficult to justify project costs or measure ROI.

Manual status reports
✅ After

Clear, data-backed visibility into resource allocation, project progress, and business impact.

Automated dashboards
Prompt Templates

Try it with these prompts

Copy any prompt and paste it directly into the tool.

Analyze AI Tool Adoption

Show me the adoption trends and usage patterns for AI coding tools like GitHub Copilot and Google Gemini across our R&D organization. I need to understand token spend metrics and identify which tools are driving the most…

Optimize AI Investment Allocation

Provide a breakdown of where AI and engineering effort is being allocated across custom categories. Help me understand the ROI of our AI investments by connecting spend, effort, and delivery outcomes.

Improve Developer Workflow

Analyze how engineers are prompting, chaining, and structuring AI interactions within the SDLC. Identify bottlenecks and suggest workflow improvements to reduce cycle times and enhance developer experience.

AI Prompts

Prompts for Project Managers

Prompt 01 Draft a Project Charter
You are an expert PMO director. Based on the following project brief, draft a complete project charter. **Project Brief:** - **Goal:** Launch a new mobile app for our e-commerce store. - **Scope:** Includes iOS and Android apps, integration…
Prompt 02 Draft a Stakeholder Update
You are the Project Manager for 'Project Alpha'. Using the following raw data points, write a concise and professional weekly status update email for executive stakeholders. Adopt a confident but realistic tone. **Data Points:** - **Project…
Prompt 03 Analyze a Burndown Chart
You are an Agile coach. This is our sprint burndown data: Day 1: 50 points Day 2: 48 points Day 3: 47 points Day 4: 40 points Day 5: 39 points Day 6: 38 points Day 7: 38 points (weekend) Day 8: 38 points (weekend) Day 9: 30 points Day 10: 2…
See all 30 AI prompts for Project Managers →
Social Proof

Trusted by 1,000+ organizations

1,000+ organizations professionals using this tool
Ease of Use
7.2
Accuracy
9.0
Value
7.4
Time Saving
8.6

"Jellyfish has transformed the way we work...team performance has increased by 30% and our delivery has become significantly more predictable."

Jaime V., SVP of Engineering · May 2026

"Jellyfish helped us uncover deeper insights into AI usage, adoption, and impact...This visibility allows us to benchmark our practices against industry standards."

Julia G., Sr. Director, TPM · Apr 2026

"We’re getting subjective info from engineers and corroborating it with objective Jellyfish metrics. The initial integration took effort, but it's paying off in morale and efficiency."

Michael R., VP of Technology · Mar 2026

"Jellyfish has dramatically improved our understanding of the reality of development across the business. We couldn’t do this without Jellyfish."

Ron T., VP Engineering · Feb 2026
1,000+ organizations+ professionals are already using this tool.
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Connects With

Jellyfish integrations

Jira GitHub GitLab Bitbucket Azure DevOps Linear Productboard Aha! GitHub Copilot Google Gemini Claude Slack PagerDuty Jenkins CircleCI
Setup complexity: Expert
Jellyfish is an engineering intelligence platform that gives project and program managers data-backed visibility into the software development lifecycle. It aggregates data from tools like Jira, Git, and CI/CD pipelines to quantify resource allocation, track progress against roadmaps, and measure the ROI of engineering initiatives, including AI adoption.
Comparison

Best Jellyfish alternatives

Jellyfish vs. LinearB: Jellyfish is a comprehensive engineering intelligence platform best suited for larger organizations focused on aligning engineering with broad business and financial strategy, including DevFinOps and AI ROI. Choose Jellyfish when you need deep resource allocation, software capitalization, and executive-level reporting. LinearB offers a more developer-centric approach, focusing on improving workflow and cycle time with real-time alerts and team-level metrics. Opt for LinearB when your primary goal is to directly improve engineering team efficiency and delivery pipelines with more immediate, tactical feedback.

You need a simpler, more lightweight metrics tool for a small team.
Your primary need is project task management, not engineering analytics.
You operate on a tight budget and need a tool with transparent, lower-cost pricing.
The decision

Is Jellyfish worth it?

Return on investment
By automating R&D financial reporting and reducing issue cycle times by a claimed 30-40%, Jellyfish aims to deliver significant ROI over its enterprise-level investment.
Built for
Engineering Managers, Product Leaders, and Technical Program Managers who need to align development work with strategic business objectives and report on team performance.
Effort to adopt
Expert
Compliance
Compliance posture not publicly documented — verify with vendor.
Who It's For

Why Project Management & Agile choose this tool

🎯
Built for
Best for data-driven project leaders in software engineering organizations who need to quantify team performance, track AI initiative ROI, and improve delivery predictability.
In-Depth Overview
For project managers, Jellyfish bridges the critical gap between engineering execution and business strategy. Instead of relying on manual updates and subjective reports, you get a live, data-driven view of your team's work by connecting directly to their tools (Jira, GitHub, etc.). The platform automatically translates technical activity into business-centric insights, such as how resources are allocated across projects or product lines. A key benefit is its ability to measure the impact of AI. Jellyfish tracks AI tool adoption, token usage, and correlates it with performance metrics, letting you prove the ROI of investments like GitHub Copilot. With customer-reported results like a "30% increase in team performance" and "30-40%" reduction in issue cycle times, Jellyfish provides the objective evidence needed to optimize workflows, improve forecast accuracy, and communicate engineering's value directly to stakeholders in finance and leadership. It moves project tracking from guesswork to data science.

Key Use Cases

📈
Identify and Clear Team Blockers
Engineering Manager
Use AI-powered insights and workflow analysis to find bottlenecks in the SDLC, reducing cycle times and improving sprint predictability.
Up to 30% faster cycle times
🎯
Improve Roadmap Predictability
Product Leader
Align roadmap priorities with real-time execution data and resource allocation to forecast delivery dates more accurately and manage stakeholder expectations.
Connect roadmap priorities to execution
💼
Justify AI Investment ROI
Program Management Lead
Track AI tool adoption, token costs, and engineering output to demonstrate the tangible business impact and productivity gains from AI initiatives to leadership.
Quantify AI's ROI
✓ Pros
Connects engineering activity directly to business outcomes and roadmap priorities.
Quantifies the impact and ROI of new AI tool adoption within engineering teams.
Provides objective data to identify bottlenecks and improve sprint predictability.
Automates financial reporting for R&D, saving significant administrative time.
Integrates with a wide range of dev tools including Jira, GitHub, and CI/CD pipelines.
· Cons
Pricing is not public and requires a demo, suggesting a high-cost enterprise solution.
Effectiveness is highly dependent on mature and consistent use of integrated tools across the team.
Focus is heavily on engineering metrics, which may be less intuitive for non-technical project managers.
Can introduce a feeling of 'big brother' monitoring if not implemented with care for team culture.
⚡ Editorial Verdict

Jellyfish provides unparalleled, data-backed visibility into the 'black box' of software development, making it invaluable for aligning engineering with business strategy. However, its power depends on comprehensive integration with your entire dev stack, meaning initial setup can be complex and its value is limited for teams with inconsistent tool usage.

Questions & Answers

Frequently asked questions

How does Jellyfish measure engineering productivity?

+
Jellyfish measures productivity by analyzing data from your engineering stack (like Git, Jira, CI/CD) to generate metrics on delivery, investment, and workflows. It focuses on outcomes like cycle time, throughput, and allocation rather than lines of code.

Can Jellyfish track the ROI of our AI tools like GitHub Copilot?

+
Yes, Jellyfish is designed to measure AI's impact. It tracks AI tool adoption, token costs, and correlates this with changes in engineering output and cycle times to help you understand and report on the ROI of your AI investments.

Is Jellyfish suitable for non-technical project managers?

+
While Jellyfish is centered on engineering data, it translates technical activities into business-aligned insights like resource allocation and roadmap progress. It's most effective for PMs comfortable with data who work closely with engineering teams.

What is the best AI tool for agile project management in a software company?

+
For agile project management in software engineering, Jellyfish is a leading AI-powered platform. It provides deep visibility into the development lifecycle by analyzing data from tools like Jira and GitHub, helping managers optimize workflows, track AI impact, and align engineering effort with business goals, with some users reporting up to 30% faster issue cycle times.

How can I use AI to measure my engineering team's performance?

+
You can use a platform like Jellyfish, which employs AI to analyze your team's activity across their entire toolchain. It automatically surfaces key performance metrics, identifies bottlenecks, benchmarks against industry data, and provides recommendations to improve productivity and delivery predictability.

Which AI tool helps connect engineering work to business outcomes?

+
Jellyfish excels at connecting engineering work to business outcomes. Its platform aggregates data on resource allocation and project progress, allowing project leaders to demonstrate how development effort aligns with strategic priorities and contributes to overall business impact.

Last reviewed:

Plans & Pricing

Jellyfish pricing and plans

Enterprise
Pricing on request
Tailored for teams and large organisations.
Contact Sales

Prices and features are updated regularly but can change at any time — always confirm on the official website. Some links on this page are affiliate links.

See all 76 AI tools for Project Managers →
Free guide

Take it with you

Getting Started with Jellyfish: A Guide for Project Managers
  • Why traditional project tracking fails for modern software teams.
  • Connecting engineering metrics (like Cycle Time) to project predictability.
  • How to map resource allocation to your strategic roadmap.
  • Measuring the true ROI of your team's AI tools (e.g., Copilot).
  • Building reports that resonate with both engineering and business stakeholders.
+4 more steps inside the guide
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AI Directory

About Jellyfish

Full Description

Jellyfish is an engineering intelligence platform that gives project and program managers data-backed visibility into the software development lifecycle. It aggregates data from tools like Jira, Git, and CI/CD pipelines to quantify resource allocation, track progress against roadmaps, and measure the ROI of engineering initiatives, including AI adoption.

Editorial Verdict

Jellyfish provides unparalleled, data-backed visibility into the 'black box' of software development, making it invaluable for aligning engineering with business strategy. However, its power depends on comprehensive integration with your entire dev stack, meaning initial setup can be complex and its value is limited for teams with inconsistent tool usage.

Last reviewed:
Disclaimer
Zekai is an independent AI tools directory. We are not affiliated with, endorsed by, or officially connected to Jellyfish unless clearly stated. All product names, logos, and brands are the property of their respective owners and are used for identification purposes only. The information on this page — including pricing, features, and availability — is general information, may have changed since our last review, and is not professional advice. Zekai Scores and verdicts are our editorial opinion. Some outbound links are affiliate links that may earn us a commission at no extra cost to you. Spotted outdated or incorrect information? Request a correction →
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