How I Built a Self Auditing Data Pipeline With Multiple LLMs
When your hotel database thinks "Game Room, Deck & Yard: Chicago Home" is a hotel, you have a data quality problem. When it happens across 212 cities in 25 countries, this isn’t a travel problem; it’s
blog.tripvento.com12 min read
klement Gunndu
Agentic AI Wizard
The rule-based gates as a free first layer before any LLM call is exactly the right order — we've built similar tiered validation where deterministic checks catch 80% of bad data before the expensive AI auditor even runs. Having the orchestrator LLM fire only on failures is a cost-control pattern more pipeline builders should adopt.