DryDock vs Jellyfish
Jellyfish is the strongest platform for explaining engineering investment to a CFO or board. DryDock answers a different question: not "where did the effort go?" but "was what shipped governed, and can I prove it?"
Jellyfish is engineering intelligence: allocation, DORA metrics, AI-impact reporting (including integrations that pull signals from Qodo and Claude Review). It is deliberately passive — a measurement layer. DryDock is an enforcement layer: policy gates that block non-compliant releases, escalations routed to humans with evidence, and a continuously-built audit trail. One reports; the other acts.
Side by side
| Jellyfish | DryDock | |
|---|---|---|
| Primary job | Measure engineering activity, allocation, and AI impact for leadership | Enforce policy, route human decisions, generate audit evidence |
| Mode | Passive: dashboards and reports | Active: clears, blocks, escalates, logs |
| AI-authored code | Reports AI impact and ROI at metadata level | Governs it: separate risk scoring and stricter gates |
| Can it stop a bad release? | No — it will tell you afterwards | Yes — that is the product |
| Audit evidence | Activity reports | Decision-level evidence log, exportable per framework |
| Human-in-the-loop | Not applicable | Policy-routed approvals with recommendations attached |
| Best buyer | VPs justifying spend to CFO / board | CTOs / VPs accountable for safety and compliance of releases |
The verdict
Choose Jellyfish to explain engineering investment upward. Choose DryDock to control what ships and prove it was controlled. They can coexist: Jellyfish tells the board where the effort went; DryDock proves the output was governed.
See governance in action
DryDock's crew of specialised AI agents enforces policy, routes human decisions, and builds your audit evidence continuously — live in your pipeline in a week.
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