Jellyfish
Software Engineering Intelligence Platform that transforms developer tool data into productivity insights for AI-integrated R&D organizations
Overview
Jellyfish is a Software Engineering Intelligence Platform designed for R&D organizations looking to measure and optimize the real impact of their engineering investments—including AI coding tools like GitHub Copilot, Cursor, and Claude. It aggregates data from 50+ developer tools (Jira, GitHub, GitLab, CI/CD pipelines, AI assistants) to provide actionable insights on team health, delivery velocity, cycle time, and resource allocation. The platform specifically addresses AI tool ROI tracking, helping engineering leaders understand whether their AI investments are actually driving higher productivity.
The Verdict
Who Should Use Jellyfish?
Best For
- Engineering leaders measuring AI tool ROI
- Mid-market to enterprise R&D orgs (50+ engineers)
- Teams tracking cycle time and velocity metrics
- Organizations needing R&D tax credit automation
- Data-driven engineering leadership
Not Ideal For
- Small teams under 50 engineers
- Startups with limited budgets
- Teams wanting quick self-serve setup
- Organizations with non-standard team structures
What's Great
- Unified view of Jira, PR data, AI usage, and team metrics
- Tracks key metrics like cycle time, throughput, and sprint velocity in one place
- AI Impact module specifically measures AI tool adoption and ROI
- Integrated DevFinOps for R&D capitalization and tax credits
- Powerful insights that enhance engineering understanding
- 9.42/10 Mid-Market Relationship Index score (highest in category)
Watch Out For
- Documentation unclear; accessing specific metrics can be cumbersome
- Complex configuration and challenging initial setup (4-8 weeks)
- Steep learning curve, relies on clean input data
- Team hierarchy management is clunky for unusual structures
- No public API for extracting engineering metrics
- Integration issues reported with Okta and Jira
Pricing
Minimum ~100 contributors. Annual contracts start at $30K+. Enterprise deployments (150+ seats) typically in low-to-mid six figures. Volume discounts available.
View all features & details
AI Impact & Productivity
- AI tool ROI tracking (Copilot, Cursor, Claude, Amazon Q)
- Enterprise-wide AI adoption roadmaps
- AI spend analysis and optimization
- Productivity correlation insights
Engineering Metrics
- Cycle time and bottleneck analysis
- Sprint velocity and throughput
- Delivery forecasting and risk detection
- Developer experience surveys
DevFinOps
- R&D software capitalization
- Tax credit automation
- Audit-ready financial reporting
- Resource allocation tracking
Integrations
- Jira, GitHub, GitLab, Azure DevOps
- Linear, Asana, Shortcut
- CI/CD platforms
- AI coding assistants
How It Compares
| Feature | Jellyfish | LinearB | Swarmia | Pluralsight Flow |
|---|---|---|---|---|
| AI Tool ROI Tracking | Yes, dedicated module | Limited | Yes | No |
| DevFinOps / R&D Credits | Built-in | No | No | No |
| Team Health Surveys | Yes | Yes | Yes | Limited |
| Minimum Team Size | ~100 devs | 10+ devs | 10+ devs | 25+ devs |
| G2 Rating | 4.5/5 | 4.5/5 | 4.6/5 | 4.3/5 |