The problem
Store teams needed fast access to internal product and process knowledge, but information was spread across systems and documents. Searching manually slowed customer conversations and daily operations.
The solution
An AI store knowledge assistant uses retrieval-augmented generation, semantic search, LLMs, approved knowledge sources, and workflow automation. Employees ask natural-language questions and receive answers grounded in product data, procedures, and internal documentation.
Key results
- 11,000 hrs/yearSaved annually
- Faster access to information in stores
- Improved employee productivity
- Better support for customer-facing teams
Benchmarks are based on the original deployment; outcomes vary by process volume, complexity, and implementation scope. Similar workflow patterns can apply to businesses of different sizes.