> For the complete documentation index, see [llms.txt](https://docs.aethra.work/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.aethra.work/risk-management/contingency-plans.md).

# Contingency Plans

In the event that primary mitigation strategies prove insufficient or external factors disrupt operations, AETHRA has prepared the following contingency protocols:

***

<details>

<summary><strong>Manual Matching Fallback</strong></summary>

**Trigger:** AI model performance drops below operational thresholds\
**Action:** Revert to human-supervised matching workflows until retraining is complete and validated

</details>

<details>

<summary><strong>Smart Contract Rollbacks &#x26; Patches</strong></summary>

**Trigger:** Discovery of a critical smart-contract vulnerability\
**Action:** Pause credential or staking functions, deploy patched contracts, and migrate data with minimal downtime

</details>

<details>

<summary><strong>Regulatory “Pause Mode”</strong></summary>

**Trigger:** Sudden legal changes (e.g. GDPR, crypto restrictions) affecting data or on-chain actions\
**Action:** Disable impacted features temporarily while legal review and engineering adjustments are made

</details>

<details>

<summary><strong>Temporary Support Scaling</strong></summary>

**Trigger:** Adoption resistance or unexpected onboarding friction causing elevated support demand\
**Action:** Expand customer success team capacity and assign dedicated account managers to pilot cohorts

</details>

<details>

<summary><strong>Emergency Infrastructure Scaling</strong></summary>

**Trigger:** Traffic or compute usage exceeds provisioned thresholds\
**Action:** Leverage burstable cloud credits, activate read-only database replicas, and deploy caching fallbacks to maintain platform responsiveness

</details>

| **Failure Scenario**        | **Fallback Action**                                 |
| --------------------------- | --------------------------------------------------- |
| AI model failure            | Manual override + retraining loop                   |
| Contract exploit            | Patch + migrate with emergency pause                |
| Legal/regulatory disruption | “Pause mode” for affected features                  |
| Spike in support needs      | Expand team, offer 1:1 onboarding                   |
| Infrastructure overload     | Cloud burst + high-availability deployment fallback |


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