video1.0<iframe src="https://www.loom.com/embed/e94746e912f14e27b6a71bf172b7fcd4" frameborder="0" width="1920" height="1440" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>14401920Loomhttps://www.loom.com14401920https://cdn.loom.com/sessions/thumbnails/e94746e912f14e27b6a71bf172b7fcd4-074b328d6aa36bf7.gif553.323This Loom walks through an internal OPTRA-IFD assignment on building and sanity-checking a rules and offer parsing workflow for Amazon customer-facing outputs. The author reuses sample CSV inputs for four routes with stackable option logic, calculates item-level offers such as cushion cover and a “final cut offer” of 4,000 rupees on a card, and verifies edge cases like missing route values and rule element gaps. They describe trade-offs including keyword matching to reduce cost and latency versus external API dependency, and LLM parser error handling when vague or unspecified values are provided. Finally, they explain PDF-based extraction to avoid manually adding hundreds of items and show checkpoints, GitHub coverage, and additional parsing inputs for resilience.