Quantify AI’s Real Contribution
See how AI affects delivery and quality with objective SDLC signals so you can validate results, guide investments, and scale what works.
Measure Meaningful Gains
Quantify improvements in speed, quality, and throughput with trusted before-and-after comparisons.
Understand Root Drivers
Connect usage, outcomes, and sentiment to explain where AI is accelerating work or creating friction.
Invest With Confidence
Use ROI and allocation patterns to decide where to scale, refine, or shift AI programs for maximum return.
Jellyfish gives us a picture of how Copilot is reshaping our organization.
Nicole Nunziata
Director of Technology Operations at Varo
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Instant Impact Summary
Generate exec-ready reports with AI-driven highlights, risks, and insights, automatically derived from your engineering data.
Causal Performance Metrics
Compare delivery speed and PR cycle time with and without AI to quantify real, measurable impact.
See Allocation Shifts
Understand how AI changes where your teams spend time, from roadmap and innovation work to KTLO.
Explore Impact Deeply
Drill into AI’s influence by individual, team, repo, or code area to answer complex questions with precision.
Assess Tool-Level Outcomes
Compare aggregate impact with specific tools to see which assistants or agents deliver meaningful results.
Track ROI Clearly
See cost efficiency, benchmark spend, and understand PR output relative to investment, so you know what’s worth scaling.
Developer Experience Signals
Layer sentiment on productivity, quality, and innovation to uncover how AI affects individual and team workflows.
Integrate Your Full AI Tech Stack
Unify insights across assistants, review agents, and emerging systems without changing existing workflows.
AI Impact Research
In-depth frameworks and guidance to support adoption, measurement, and scaling of AI.
4.5/5 on G2
4.8/5 on Gartner