InteliG vs Jellyfish: Execution Intelligence Without the Enterprise Overhead

If you’re evaluating Jellyfish, you’ve already identified the problem: your engineering org is a black box to leadership. Money goes in, software comes out, and nobody can explain the relationship between the two.

Jellyfish tries to solve that. So does InteliG. But the approaches are fundamentally different — and so are the results.

What Jellyfish Does

Jellyfish is an engineering management platform built for enterprise. It aggregates data from Jira, GitHub, CI/CD tools, and calendars, then surfaces capacity planning, resource allocation, and investment reporting for engineering leaders.

It’s good at what it does. If you’re a VP of Engineering at a Fortune 500 company and you need board-ready slides showing how engineering time maps to strategic initiatives, Jellyfish will get you there.

The product is built around the idea that engineering leadership needs better visibility into where time and money are going. Fair premise. But the execution tells you who the real customer is: procurement teams with six-figure budgets and twelve-month implementation timelines.

The Enterprise Problem

Jellyfish is enterprise software in every sense of the word. Long sales cycles. Dedicated implementation teams. Custom integrations. Annual contracts that start well into six figures.

That’s not a criticism of their business model — it’s a description of their market. If you’re running a 2,000-person engineering org and you need a platform that speaks the language of portfolio management and executive reporting, Jellyfish fits.

But most CTOs don’t run 2,000-person orgs. Most CTOs run teams of 10 to 200, and they don’t need portfolio allocation dashboards. They need answers.

Why did velocity drop last month? Which initiative is actually delivering value? Where is the money going? What decision did we make six months ago that created the technical debt we’re paying for now?

Dashboards don’t answer questions. They generate more of them.

The Jira Dependency

Here’s the deeper issue: Jellyfish still treats Jira as the system of record for engineering work. Ticket status, sprint velocity, story points — the entire analytical foundation rests on data that engineers manually update (or don’t).

We’ve written extensively about why this is broken. Tickets reflect intent, not reality. The gap between what Jira says happened and what actually happened in the codebase is where every meaningful insight lives.

InteliG uses Git as truth. Commits, pull requests, deployments, code changes — these are facts. They happen automatically. They can’t be gamed by dragging a ticket to “Done” on Friday afternoon. When you build intelligence on top of Git, you’re building on a foundation that doesn’t require anyone to remember to update a board.

What InteliG Does Differently

InteliG isn’t a dashboard platform. It’s a reasoning engine.

The core of InteliG is Cognis — an AI system that ingests your Git data and connects it across five pillars:

• Code Intelligence: What’s actually changing in your codebase, who’s driving it, and what patterns emerge over time.
• Strategy: Initiatives tracked through commits, not tickets. ROI grades based on what shipped, not what was planned.
• Finance: Cost per contributor, investment distribution across initiatives, and the actual return on engineering spend.
• Knowledge: Meeting decisions, architectural choices, and rationale — linked directly to the code they produced.
• Cognis (AI): Ask a question in plain language. Get an evidence-backed answer sourced from your own engineering data.

You don’t log in and stare at charts. You ask Cognis: “Why did our deployment frequency drop in February?” and it reasons across commits, contributor patterns, and initiative timelines to give you an answer with evidence.

That’s the difference between execution intelligence and analytics.

Self-Serve vs. Enterprise Sales

Jellyfish requires a sales conversation, a scoping call, an implementation phase, and probably a dedicated customer success manager. That’s appropriate for their price point and their customer profile.

InteliG is self-serve. Connect your GitHub org. Cognis starts ingesting. Ask your first question in minutes, not months.

No procurement process. No implementation team. No six-figure annual contract. You connect your data source, and the reasoning engine goes to work.

This isn’t about being cheaper — it’s about being faster to value. A CTO evaluating tools on Monday should have answers by Tuesday, not by next quarter.

When Jellyfish Makes Sense

If you’re a large enterprise with dedicated engineering operations teams, an existing Jira-centric workflow you’re not willing to change, and a budget for premium tooling with white-glove support — Jellyfish is a reasonable choice.

When InteliG Makes Sense

If you’re a CTO who wants intelligence instead of dashboards. If you believe Git is a better source of truth than Jira. If you want to ask questions and get answers, not interpret charts and build your own narratives. If you want to connect strategy to code to finance without a six-month implementation.

InteliG was built for the CTO who runs a real engineering org and needs to make real decisions — not present slides.

Connect GitHub and ask Cognis →