> For the complete documentation index, see [llms.txt](https://docs.hivel.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.hivel.ai/ai-adoption/hivel-surge-ai-roi-dashboard-overview/recovery-r-money-you-could-have-saved.md).

# Recovery (R) — Money you could have saved

The Recovery pillar quantifies waste and surfaces opportunities to reduce spend without cutting capability. It identifies four distinct waste categories:

* **Zombie Sessions** — AI agent runs that produced no commits or output
* **Idle Licenses** — seats paid for but never used in the period
* **Stale Code** — AI-generated lines that were committed but never merged or immediately reverted
* **Model Misselection** — sessions where an expensive model was used for tasks a cheaper alternative handles equally well

See total recoverable spend across your organization and drill down to the team and model level. Compare accepted versus rejected AI-generated code to measure output quality and spot teams struggling with AI integration. This pillar transforms abstract "waste" into concrete dollar figures.

**Key metrics:**

* Total Recoverable — aggregate savings potential across all waste categories
* Productive vs. Recoverable Spend — stacked view showing real output versus waste, by team or model
* AI LOC Accepted vs. Not Accepted — lines of code generated but rejected, with cost visibility
* Recovery Opportunity Map — treemap visualization showing waste distribution by category and team

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