Weave vs Jellyfish: which engineering intelligence platform is right for your team?
Both Weave and Jellyfish help engineering leaders measure productivity and AI impact. The difference is what they measure. Weave reads the work itself, using LLMs and machine learning on every PR, review, and deploy. Jellyfish builds metrics from Jira tickets and PR metadata. Here's the full breakdown.
The short version
Weave measures human and AI contributions directly from code, across every PR, review, and deploy, normalized into a single output unit calibrated to expert benchmarks. Jellyfish turns Jira and Git metadata into allocation, delivery, and AI adoption metrics.
Teams typically choose Weave when they want objective, code-level measurement of engineering output and AI ROI, with same-day setup and transparent pricing: a free tier, and Pro at $50 per engineer. Teams typically choose Jellyfish when Jira-based resource allocation reporting and finance workflows are the priority.
At a glance
How Weave and Jellyfish compare
Compare
Weave
Jellyfish (jellyfish.co)
Core approach
LLMs + domain-specific ML read the code itself
Analytics built on Jira tickets and PR metadata
AI vs. human attribution
Built in: every contribution attributed at the code level
AI adoption, usage trends, and token spend tracking
Measurement unit
Normalized units of work, calibrated to expert benchmarks, not line counts
DORA, SPACE, and AI metrics plus allocation reporting
Code quality insight
Quality, review intelligence, and code turnover measured from the code
Cycle time and throughput from issue and PR signals
Time to value
Live before the end of the day; self-serve signup
Sales-led onboarding with guided rollout
Pricing
Transparent: free Starter, $50/engineer Pro, custom Enterprise
Seat and module based; quote only via sales
AI agent for insights
Wooly: ask anything about your engineering org
Jellyfish AI Assistant
Finance reporting
Dev FinOps built on measured output
DevFinOps: capitalization and R&D tax credits
Compliance
SOC 2 Type II, GDPR, HIPAA, SSO/OIDC, SCIM
Enterprise security, SOC and ISO certifications
Scale
500+ organizations incl. Fortune 100; 2M+ PRs analyzed; 20,000+ engineers
Enterprises incl. Box, DraftKings, and Priceline
What is Weave?
Weave is the engineering intelligence platform for the AI era. It uses LLMs and domain-specific machine learning to understand engineering work at the source: the code itself. It normalizes that work into a single unit of output, calibrated to expert benchmarks rather than line counts or story points. Because Weave reads the work directly, it can tell you things ticket metadata can't: how much of your output was written by AI versus humans, which AI tools are actually helping your team ship faster, and whether AI is affecting code quality and review load. Weave is trusted by 500+ organizations, from seed-stage startups to Fortune 100 companies.
What is Jellyfish?
Jellyfish (jellyfish.co) is a software engineering intelligence platform that turns data from tools like Jira and Git into metrics for delivery, resource allocation, and AI adoption. Its patented allocation model maps engineering effort to business priorities, and its DevFinOps product automates software capitalization and R&D tax credit reporting for finance teams. Jellyfish is a credible, established platform used by enterprises like Box, DraftKings, and Priceline. The question isn't whether Jellyfish is good. It's whether ticket-level metrics can still describe engineering work now that AI writes a growing share of the code.
The key difference
Measuring the work vs. measuring the tickets
Jellyfish's approach
Jellyfish turns Jira tickets and PR metadata into delivery and allocation metrics. That describes process well: cycle times, throughput, and where effort is going. But a ticket count can't tell you what the code actually did, how good it was, or whether a human or an AI agent wrote it.
Weave's approach
Weave analyzes every PR, review, and deploy as it happens. LLMs and domain-specific ML, tuned to your codebase, evaluate the actual engineering work, attribute it to humans or AI, and normalize it into a benchmarked unit of output. No proxy metrics. No story-point inflation. No blind spots when agents ship code without tickets.
If your team ships with Cursor, Claude Code, Copilot, or autonomous agents, more and more of your real output never maps neatly to a ticket. Measuring the work itself is the only way to see it.
Why Weave
Why teams choose Weave over Jellyfish
Code-level truth, not ticket proxies
Tickets and story points describe intentions. Weave reads the code that actually shipped, evaluates its complexity and quality, and turns it into a normalized output unit you can compare across teams and time.
Real AI attribution, not just adoption
Jellyfish tracks AI tool adoption and token spend. Weave goes further: it attributes every contribution to AI or humans at the code level, so you know what AI actually produced, not just that it was used.
Agent-ready by design
Autonomous agents ship code that never touches a Jira board. Weave's agent observability measures that work the same way it measures human work, so your metrics don't go dark as agents scale.
Live before the end of the day
Weave is self-serve: connect your tools and see data the same day. Reducto went from install to first executive report in 60 days and measured a 19% increase in output. Jellyfish onboarding is sales-led with guided rollout.
Transparent pricing with a real free tier
Weave publishes its pricing: a free Starter plan, Pro at $50/engineer per month, and custom Enterprise plans. Jellyfish prices by seat and module, and you won't know the number until you've talked to sales.
Enterprise-grade from the start
SOC 2 Type II certified, GDPR and HIPAA compliant, SSO/OIDC, SCIM provisioning, and regular third-party audits, all without an enterprise sales cycle to get started.
When Jellyfish might be the better fit
We'd rather you pick the right tool than just pick us. If your organization runs on Jira-centric planning and your top priority is mapping engineering effort to business initiatives, Jellyfish's patented allocation model and scenario planning are mature and well liked by product and finance stakeholders. Finance reporting alone shouldn't decide it, though: Weave includes Dev FinOps as well, built on measured output rather than ticket estimates. If you want engineering measurement built for the AI era, with objective, code-level attribution you can defend in front of a board, that's what Weave was built for.
Customer Story
"Our goal is to ship the highest quality product as fast as possible for our customers. We use Weave to get an objective measurement and keep ourselves honest about how we're doing."
Raunak Chowdhuri
Founder & CTO, Reducto
+19%
Increase in measured engineering output
60 days
From install to first executive report
Frequently asked questions
What's the main difference between Weave and Jellyfish?
Weave measures engineering work directly from code using LLMs and machine learning, attributing every contribution to humans or AI and normalizing output against expert benchmarks. Jellyfish builds delivery, allocation, and AI adoption metrics from Jira tickets and PR metadata. Weave measures the work itself; Jellyfish measures the process around it.
Is Weave or Jellyfish better for measuring AI coding tools like Cursor, Claude Code, and Copilot?
Weave is purpose-built for AI measurement: it attributes code to specific AI tools, quantifies AI's impact on velocity, quality, and review throughput, and provides observability for autonomous coding agents. Jellyfish tracks AI adoption, usage trends, and token spend, which tells you AI is being used but not what it produced at the code level.
How much do Weave and Jellyfish cost?
Weave publishes transparent pricing: a free Starter plan, Pro at $50 per engineer per month, and custom Enterprise pricing. Jellyfish does not publish prices. Its pricing is based on seats and the modules you select, quoted through its sales team.
How long does it take to get started with Weave vs Jellyfish?
Weave is self-serve: teams connect their tools and are live before the end of the day, with no sales call required. Jellyfish onboarding is sales-led, typically starting with a demo, quote, and guided rollout.
Does Weave handle software capitalization like Jellyfish DevFinOps?
Yes. Weave includes Dev FinOps for engineering cost and investment reporting, built on measured output rather than ticket estimates. Jellyfish DevFinOps is a mature product for software capitalization and R&D tax credits, and a reasonable choice if finance reporting is your primary use case.
Is Weave enterprise-ready?
Yes. Weave is SOC 2 Type II certified, GDPR and HIPAA compliant, and supports SSO (OIDC) and SCIM provisioning, with regular third-party audits. It's used by Fortune 100 companies and supports GitHub Enterprise.
Can I switch from Jellyfish to Weave?
Yes. Weave connects directly to your existing tools, including GitHub and your project management stack, and calibrates automatically to your codebase. Most teams see their first data the same day. Book a demo and we'll map your current Jellyfish reporting to Weave equivalents.
Measure the work itself, not the tickets around it
Weave normalizes engineering work into a single unit, calibrated to expert benchmarks. No proxy metrics, no sales cycle to get started, no guesswork.
The engineering intelligence platform for the AI era.
Trusted by engineering teams from seed stage to Fortune 500