Expanded Jellyfish AI Impact unifies usage, spend, and impact data from multiple AI tools so leaders can measure ROI, guide AI strategy, and ensure investments deliver tangible value
BOSTON, August 26, 2025 — Jellyfish, the leading Software Engineering Intelligence Platform, today launched new features for Jellyfish AI Impact that deliver end-to-end visibility of the impact of AI on productivity, quality, and value across the software development lifecycle (SDLC). With this expanded suite of solutions, engineering leaders can measure their organization’s return on AI investments, optimize their AI spend, scale adoption, and guide AI strategy with confidence.
Jellyfish’s 2025 State of Engineering Management report found that 90% of teams are embracing AI coding tools to augment their engineering practices, a significant increase from last year when 61% said their engineering organizations had embraced AI. But many engineering teams are still flying blind with AI, lacking the data necessary to build the most effective AI tool stack or tie spend directly to outcomes.
As the pricing models for AI coding tools shift and C-suite leaders seek proof of their business value, Jellyfish is the only platform providing vendor-agnostic, SDLC-wide visibility into AI adoption, spend, and impact.
“Engineering leaders need data to decide which AI tools to invest in, expand, or retire,” said Andrew Lau, CEO and co-founder of Jellyfish. “Jellyfish AI Impact lets you compare tools, understand who’s using them and how, and connect AI investment directly to project outcomes. As the industry continues into the agentic era, we give you the insight you need to optimize today’s tools and prepare for what’s next.”
The new features for Jellyfish AI Impact – which now supports Anthropics’ Claude Code and Windsurf in addition to GitHub Copilot, Cursor, Gemini, and Amazon Q – include:
- Multi-Tool Comparison: Right now, companies don’t know which AI tool is best for which activity or where to invest their money. Jellyfish pulls data on tool adoption, cost, and impact into one consolidated view so users can benchmark multiple AI tools, identify the highest-value tools for specific use cases, and build the most effective AI tool stack.
- Code Review Agent Insights: With a growing number of companies using code review tools, Jellyfish allows teams to measure the impact of AI code review agents like CodeRabbit, Graphite, and Greptile across the full SDLC.
- AI Spend Insights: With Jellyfish’s real-time, usage-based spend data, companies can now tie AI spend directly to outcomes to determine ROI at the team, individual, and initiative level.
Jellyfish AI Impact combines adoption metrics, dynamic value tracking, and delivery outcome data across all AI-powered tools – from coding assistants to code review agents – for a clear, comprehensive view of AI’s role in software delivery. With these holistic insights, engineering leaders can drive smarter investments and better delivery outcomes across the SDLC.
To see the new features for Jellyfish AI Impact in action, request a demo today.
About Jellyfish
Jellyfish is the leading Software Engineering Intelligence Platform, helping 500+ companies including DraftKings, Keller Williams and Blue Yonder, leverage AI to transform how they build software. By turning fragmented data into context-rich guidance, Jellyfish enables better decision-making across planning, developer experience and delivery so R&D teams can deliver stronger business outcomes.
###
