Hybrid AI Triage System Beats Pure LLM Approach in Ops Ticket Classification

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A developer has completed a key evaluation phase of ops-triage-ai, an operational triage project that combines a deterministic baseline with a local LLM. Testing on a frozen held-out set of 70 synthetic tickets showed category accuracy improving from 82.9% to 95.7%, while HIGH/CRITICAL priority recall rose from 78.6% to 100%. Notably, the deterministic baseline outperformed the LLM in certain areas, leading the project to adopt a hybrid architecture rather than a full AI replacement. The system routes 51.4% of cases to human review and maintains a full audit trail covering ticket, run, decision, and feedback. The project concludes that knowing where a model falls short is as valuable as knowing where it succeeds.

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