Jellyfish

Engineering intelligence platform that analyzes developer tool data to measure AI impact and team productivity

Verified API available ~3.2k monthly visits
Quick facts
What is it Engineering intelligence platform that analyzes developer tool data to measure AI impact and team productivity
Pricing Contact for Pricing
Free tier No
Platform Web Application
API Yes
Best for measuring AI tool adoption and effectiveness across engineering teams, optimizing resource allocation for software projects
Domain registered 2015

Data updated Aug. 1, 2026

What does Jellyfish do?

Jellyfish is an engineering intelligence platform that collects and analyzes data from developer tools to provide insights into team performance and AI adoption. It connects to systems like Jira, GitHub, GitLab, and various AI coding assistants to give engineering leaders a comprehensive view of how their teams work. The platform tracks everything from code commits and pull requests to AI tool usage patterns, helping organizations understand where their engineering efforts are most effective.

The system works by integrating with existing development tools without requiring teams to change their workflows. It measures key engineering metrics based on established frameworks like DORA and SPACE, providing benchmarks for team performance. What makes Jellyfish particularly relevant today is its focus on AI impact measurement—it helps companies track how coding assistants and AI tools affect productivity, code quality, and development speed across different teams.

Engineering managers and R&D leaders benefit most from Jellyfish when they need to make data-driven decisions about resource allocation, tool investments, and team structure. Real-world use cases include identifying bottlenecks in development workflows, demonstrating the ROI of AI tool investments to stakeholders, and maintaining compliance with financial reporting requirements for R&D tax credits. The platform helps organizations move from guessing about engineering productivity to measuring it with concrete data.

#ai adoption#developer productivity#devops-analytics#engineering-intelligence#resource allocation#software-metrics

Key features

What makes it stand out
01
AI impact measurement to track adoption and ROI of coding assistants
02
Developer productivity insights combining system data and team feedback
03
Engineering metrics standardization based on DORA and SPACE frameworks
04
Resource allocation visibility for priority project tracking
05
Automated financial reporting for R&D tax credits and capitalization

Who is Jellyfish for?

Who benefits most from this tool
measuring AI tool adoption and effectiveness across engineering teams
optimizing resource allocation for software projects
automating engineering financial reporting and compliance

Trust & presence

Domain Domain registered 2015

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