GenAI pilots often stall at the last mile—reliability. HP ships a hybrid AI reliability layer that fuses generative AI with predictive ML and humans-in-the-loop to make deployments robust. Samaresh shares the production patterns HP use across HP platforms (e.g., Z Boost, AI Studio, Hydra): guardrail policies that expand over time, retrieval and output validation with predictive models, confidence-aware routing between GenAI/predictive/HITL, and telemetry (success rate, hallucination/override rate, p95 latency, cost). Attendees get a reference architecture, rollout playbook (canary/shadow), and KPI templates to move from demo to dependable—turning AI’s potential into realized value.