# Towards ROI based Systems ## Self Hosted Architecture and Self Correcting Models ### ROI Projections **Quality Improvements:** * **Error reduction**: Target 80% reduction in production errors * **User satisfaction**: Increase from current baseline to 95% satisfaction * **System reliability**: 99.9% uptime with quality guarantees * **Cost efficiency**: Integration with $35k/month infrastructure savings ### Current Investment **Infrastructure Costs:** * **Correction model hosting**: Integrated with existing 48 NVL-72 infrastructure * **Evaluation framework**: LangFuse integration and custom tooling * **Monitoring systems**: Extension of existing observability stack * **Development resources**: Dedicated team for correction system development **Projected Savings:** * **Reduced human review**: 70% reduction in manual quality assurance * **Improved user satisfaction**: 25% increase in user retention * **Decreased support costs**: 40% reduction in user-reported issues * **Enhanced reliability**: 50% reduction in critical system errors *** ## LRMs as a Judge ### ROI Projections **Quality Improvements:** * **Content quality increase**: Target 40% improvement in average quality scores * **Error reduction**: 60% decrease in quality-related user complaints * **Consistency improvement**: 90% reduction in quality score variance * **Time to market**: 50% faster content approval and deployment cycles **Cost Savings:** * **Reduced human review costs**: $200k annual savings in quality assurance labor * **Decreased user support**: 30% reduction in quality-related support tickets * **Improved user retention**: 15% increase attributable to higher content quality * **Infrastructure efficiency**: Integration with existing compute resources minimizing additional costs --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://sully.gitbook.io/sully.ai-docs/FEM1tMOJsSSszbLOgKLA/towards-roi-based-systems.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.