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Hivel measures AI-generated code that survives review and reaches production. Jellyfish relies on surveys and surface signals, which are outdated and cannot confirm how much AI code actually ships.
Without an accurate adoption baseline, AI impact and ROI calculations remain incomplete and difficult to defend.
Jellyfish is designed for financial visibility, headcount allocation, and planning. It is not built to diagnose delivery bottlenecks or execution issues inside the SDLC.
No. Jellyfish focuses on descriptive dashboards. It does not guide teams on where to intervene or which changes will improve outcomes.
Jellyfish depends on modeling teams, initiatives, and financial structures before insights appear, which increases setup effort and delays value.
Most teams see value in under 48 hours once integrations and access are in place. Jellyfish typically requires weeks of survey setup.
Yes. With SOC2 and SSO/SCIM compliance and role-based access controls, Hivel is an ideal partner for global enterprises, helping many public companies in the US, Europe, and globally.
Yes. Hivel supports VPC and on-prem deployments.
Hivel connects to your existing engineering stack, including Git, task tracking like Jira, calendars, code quality tools, and AI coding tools, to combine code, delivery, and AI usage data into one executive view.
You get dedicated DevEx Engineers who work closely with your team to interpret data, audit hygiene, deliver custom insights based on your use cases, and help you achieve defined goals over time.

