Engineering Intelligence for Your AI-Native SDLC

See how your people and agents really build software

Connect AI usage, cost, and capacity to real outcomes, benchmarked against 1,000+ engineering orgs.

More code isn't the same as more value

AI can double the code moving through your pipeline. It also creates new bottlenecks in review and CI, new costs in tokens and seats, and new questions from finance and the board. Metrics built for human-only teams can’t tell you which changes are helping.

“Rolling out AI tooling without measurement is just hope. Jellyfish gave us the data to see what was actually working, where adoption was real, and how it translated into output across the org.”

Jim Turpin

VP of Engineering at Arcadia

“Jellyfish has transformed the way we work…team performance has increased by 30% and our delivery has become significantly more predictable. It has bridged the gap between engineering, product, and finance, allowing us to connect our technical efforts directly to business priorities.”

Jaime Vivas

SVP of Engineering at Siigo

See Customer Story

“Roughly 80% of our code is now generated by AI with up to 30% faster issue cycle times, but AI also introduced new bottlenecks we hadn’t anticipated…when a transformation is moving this fast, operating blind isn’t an option. Jellyfish gave us the data to understand where we were seeing real ROI, where the new constraints were emerging, and how to stay in control of something that’s genuinely changing in front of our eyes.”

Ron Ben Yosef

VP, Technology & Business Operations at Loadsmart

Product Capabilities

One platform for every question about AI and engineering

Turn engineering data into answers you can act on

Every engineering metric, human and agent, in one place

Explore throughput, cycle time, and DORA metrics across people and agents. Start from Blueprints, build custom metrics in plain English, or go straight to SQL.

Explore Metrics & Reporting

See how teams really work with AI, then scale what works

Track skill adoption, agent sessions, and the tasks engineers hand off. Compare cohorts to find what your best teams do differently.

Explore AI Workflow Intelligence

Know what AI costs, what it pays for, and what it returns

See spend across every vendor, team, and model, reconciled and tied to outcomes. Neutral numbers, ready for finance and the board.

Explore AI ROI

Hear from the people doing the work

Research-backed surveys show where friction slows teams down, right next to delivery and AI data. Catch burnout before it costs you.

Explore DevEx

Get a Demo

Ask your data for insights. Take action.

Get plain-language answers and root causes from your engineering data. Then let agents build dashboards, monitor what matters, and flag what needs attention.

Jellyfish Assistant

How much is our team spending on tokens?

Here’s your AI spend for the current month:

Claude — $18.4K, 61% of total token spend
GitHub Copilot — $6.2K across 240 active seats
ChatGPT / OpenAI — $3.1K, mostly ad hoc usage

Is that trending up or down?

Total spend is up 14% month over month, driven by code review and agentic workflows. Cost per merged pull request is down 9% over the same period, so each dollar is going further than it did in Q1.

“When I asked for a team’s average velocity, [Jellyfish Assistant] didn’t just give me a number, it provided key insights and actionable recommendations that were spot on.”

Joe Donovan Senior Program Lead, Precisely

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Jellyfish Research

Benchmark against 1,000+ engineering organizations

Jellyfish draws on 100M+ pull requests, 90M+ prompts, and 150T+ tokens from real-world engineering teams to reveal what’s changing, what works, and where teams stand. Explore original research, benchmarks, and practical resources for modern engineering leadership.

research

Jellyfish AI Engineering Trends

Explore this first-of-its-kind report on how ai is impacting the SDLC, based on data from 100M+ PRs.

See the Trends

webinar

AI Impact Week

Explore keynotes, product demos, and expert discussions on how leading teams measure, improve, and prove AI’s impact.

Watch the sessions

research

2026 State of Engineering Management

Insights from 600+ engineering leaders on how top AI adopters are pulling ahead.

Explore the data

“The visibility Jellyfish provides allows us to benchmark our practices against industry standards and demonstrate to key stakeholders how Box is leveraging AI responsibly and productively.”

Julia Gan

Sr. Director, TPM and Engineering Chief of Staff, Box

Enterprise & Security

Built for enterprise engineering

Visit the Trust Center

Certified

SOC 1 Type II, SOC 2 Type II, GDPR, CCPA, and CSA STAR certifications and attestations.

Secure

Encryption at rest and TLS 1.2+ in transit, role-based access controls, least-privilege access, and ongoing third-party security testing.

Adaptable

Flexible integrations, configuration, and deployment options that fit your existing engineering environment.

Supported

Dedicated onboarding, Jellyfish Academy, and professional services to help you get value fast.

“Jellyfish stood out as the more mature, enterprise-ready product. Its strong drill-down capabilities, team-focused metrics, and robust transparency were game-changers.”

Uli

VP Engineering, Lightspeed

Answer the three questions every AI investment faces

Where do I stand?

See human, AI-assisted, and agent work side by side, in the metrics you already trust.

Am I transforming?

Find out which teams are compounding with AI and which are spinning their wheels.

What is it worth?

See what AI costs, what it pays for, and what it returns.

See your AI-native engineering org clearly

Bring your hardest questions about AI, capacity, and cost. We’ll show you the answers in your own data.

Get a Demo Tour the Product