Same Saavi narration, smaller file. Opus 48k preferred — auto-selected by your browser.
Scenario anchor
Aaranya IT ke ek large BFSI client ka scenario sochiye — ek agentic customer-support
pipeline hai jo loan restructuring queries handle kar raha hai. Agent ne ek
customer ko incorrect EMI waiver eligibility bata di, kyunki kisi ne
confidence threshold set hi nahi kiya tha — directly LLM output production
mein chala gaya. Aap is lesson mein dekhenge ki confidence-gate kaise ek
circuit breaker ki tarah kaam karta hai: low-confidence responses ko
automatically human reviewer ke paas escalate karo, before irreversible
downstream actions trigger ho jaayein.
Key Takeaways
Define per-intent confidence thresholds, not a single global value — a loan-waiver intent threshold must be set tighter than an order-status lookup, matching the blast radius of a wrong answer.
Pair confidence score with secondary signals — policy-schema validation, entity extraction completeness, and tool-call success/failure — so the escalation gate catches high-confidence hallucinations that a raw score alone would pass.
Design the human-in-the-loop path as a first-class production route, not an exception handler: queue SLA, reviewer context payload, and audit trail must be specified in the architecture document before go-live.
Memory anchor: confidence-gate = circuit-breaker-threshold — just as a circuit breaker trips on error-rate, the confidence-gate trips on low-certainty, rerouting traffic to a stable human fallback before cascading damage occurs.