How Human-in-the-Loop Improves Model Reliability

Deploying AI in production is not a one-time event; it is a continuous cycle. Model drift and edge cases inevitably degrade performance over time.

We champion a robust Human-in-the-Loop (HITL) strategy integrated directly into the MLOps pipeline. Low-confidence predictions are routed to human experts.

This creates a virtuous cycle of Active Learning, ensuring your AI remains reliable as real-world conditions evolve.