Tyson Foods elevates customer search experience with an AI-powered conversational assistant built on Amazon Bedrock
Tyson Foodservice had limited direct engagement with over 1 million unattended operators who purchased through distributors without direct company relationships, and its keyword-based search frustrated foodservice professionals by failing to match culinary terminology to catalog descriptions, driving lost revenue opportunities.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · User submits search query
A user uses the search bar on the Tyson Foodservice website to submit a query.
Tools used
Amazon BedrockLangGraph
Outcome
Tyson Foodservice deployed a generative AI assistant and semantic search on its website, enabling direct engagement with previously unattended operators, dramatically improving search relevance, and capturing high-value customer interaction data for business intelligence.
What failed first
The earlier keyword-based search on the Tyson Foodservice website failed to handle terminology mismatches, causing chefs searching for 'pulled chicken' to miss products labeled 'shredded chicken,' and those looking for 'wings' to miss 'party wings' or 'drummettes.'