Agentic Catalog Orchestration

Traditional PDPs assume a human scrolls, reads, and compares. Agentic workflows collapse that path: agents need structured eligibility signals, compatibility truth, and citation-grade facts. Ambiguous data causes agents to deprioritize or skip offers entirely.

A layered model: (1) canonical product graph with stable IDs and attribute normalization, (2) decision-grade copy blocks (what is included, exclusions, compatibility) separated from marketing prose, (3) retrieval policies that prefer verified facts over generative filler, and (4) evaluation harnesses that score agent success rates by scenario—not keyword rank.

Early experiments correlate structured catalog upgrades with higher agent citation rates and fewer hallucinated claims in downstream assistants. The lab tracks scenario coverage, abstention rate, and post-edit correction cost as leading indicators.