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Apolla AI
A retail chain

Retail

Store managers spend 70% less time on reports, store-walk issue closure up from 40% to 92%

Retail chain: a store operations Agent that turns store walks and daily reports into one conversation

Challenge

Managers at more than eight hundred stores filled in 6 reports a day, answered a stream of questions from regional managers and handled tasks pushed down from head office. Issues found on store walks were noted in group chats and mostly never followed up. Head office always saw store status a day late.

The company wanted to get store managers back onto the sales floor: hand off the administrative work, and give head office a real-time view of what was actually happening in stores.

Approach

Store managers, field supervisors and head office each got their own entry point, all running on one store operations Agent underneath.

  • Store managers: report the day's trading by voice, and the Agent generates the daily report and syncs it to every system; questions on stock, promotions and rosters are answered instantly
  • Supervisors: store-walk photos and voice notes become an issue list automatically, assigned to a person and tracked to closure
  • Head office: store status rolled up by region and format, with automatic alerts on outlier stores
  • Tasks are issued and completion confirmed in the same conversation

Architecture highlights

Integrated with POS, inventory, rostering and WeCom (enterprise WeChat). Stores use a lightweight mobile client that compresses photos on the device before upload. Issue lists and tasks share one state machine, so every role sees a consistent view.

Customer feedback

A store manager's phone used to hold six apps and ten group chats. Now it holds one chat window.
Vice President of OperationsA retail chain

Want more detail on this project?

In a workshop we can share the architecture decisions, the pitfalls and the actual timeline.