Jellyfish
Jellyfish is a Software Engineering Intelligence Platform that unifies data from various developer tools to provide comprehensive insights into engineering productivit…
Our verdict
Who it's for
Transform developer tool data into actionable productivity insights for R&D in the AI era.
Who should look elsewhere
No free tier or public pricing information available, requiring a demo for cost details.
Pros
- +Provides a comprehensive, unified view of engineering performance across the SDLC.
- +Helps identify and resolve bottlenecks, leading to increased throughput and predictability.
- +Automates financial reporting for R&D, saving time and ensuring compliance.
- +Offers insights for improving developer experience and team satisfaction.
- +Supports data-driven coaching and 1:1s for engineering managers.
Cons
- −No free tier or public pricing information available, requiring a demo for cost details.
- −Requires integration with existing tools, which might involve initial setup effort.
- −Focuses heavily on engineering metrics, which might be less relevant for non-technical roles.
Key features
- ✓AI Impact Measurement (adoption, spend, productivity, speed, quality)
- ✓Developer Productivity Insights (bottleneck identification, focus/flow improvement)
- ✓Standardized Engineering Metrics (DORA, SPACE framework)
- ✓Resource Optimization and Allocation Visibility
- ✓Delivery Predictability (capacity data, risk alerts, scenario modeling)
- ✓Engineering Effort Alignment with Strategic Priorities
- ✓Team Performance Metrics, Trends, and Recommendations
- ✓Developer Experience Improvement (survey insights, workflow friction identification)
Pricing
| Plan | Price | Billing | Notes |
|---|---|---|---|
| Contact Us | — | month | Engineering Management; AI Impact; Team Effectiveness |
Integrations
GitHubJiraLinear