Part 5: The Self-Reflection Critique Loop: Preventing Hallucinations in E-commerce Search

← Previous Chapter: Part 4: Active RAG & Strict Tool Calling | Series Hub | Next Chapter: Part 6: Production Operations & Semantic Caching → Prerequisite: Review Part 4: Active RAG & Strict Tool Calling: Connecting LLMs to Real-Time Inventory APIs for live microservice data injection. Answer-first: The self-reflection critique loop deploys a dual-tier verification architecture combining sub-millisecond deterministic Golang constraint validators with LLM semantic reflection, slashing catalog hallucination rates below 0.05%. When candidate products violate user price ceilings or technical specifications, autonomous re-search triggers reformulate payload filters within a bounded two-iteration recursion ceiling, guaranteeing response accuracy without breaching the 200ms interactive user SLA. ...

LeaseInVietnam: AI-Powered Expat Rental & B2B Lead Engine

LeaseInVietnam: AI-Powered Expat Rental & B2B Lead Engine Answer-first: LeaseInVietnam integrates AI property search, automated contract processing, neighborhood intelligence, and localized expat data pipelines to simplify long-term rental discovery. Most AI content projects are built around one question: how do I publish more? LeaseInVietnam is built around a different question: how do I make every published piece convert? The system is an autonomous relocation hub targeting expats and digital nomads renting in Southern Vietnam — Ho Chi Minh City, Nha Trang, Phú Quốc. It produces content in American English, publishes daily via GitOps, and routes every reader interaction toward a B2B lead funnel that pays commission on moving services, cleaning bookings, furniture rentals, and legal consultations. ...