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Conversational AICase study

Internal Team Concierge Bot

Internal concierge workflow that collects requester name and location, routes operational requests into maintenance, inventory, or shift swap paths, captures path-specific details (equipment/fault/urgency for maintenance, item/quantity for inventory, role/reason for shift swaps), generates request references, logs each request to Google Sheets, sends Slack notifications for visibility, and offers a post-submit menu to return to the main menu or end the session.

Conversational AI · workflow canvasproduction build
Internal Team Concierge Bot workflow

Context

Teams needed a single internal entry point for common operational requests (maintenance, inventory, shift swaps) with structured data capture, consistent logging, and immediate Slack visibility for follow-up.

Approach

Built a Botpress workflow that starts with a greeting and location capture, presents a main menu to route into maintenance, inventory, or shift swap paths, collects detailed fields per path and generates request references, logs each request to Google Sheets, sends categorized Slack notifications for operational visibility, and includes a post-submit menu allowing users to submit another request or end the session, with a fallback node for unrecognized request types.

Architecture

  1. greeting
  2. location_select
  3. main_menu
  4. path_maintenance (equipment, fault, urgency)
  5. confirm_maintenance
  6. log_maintenance_sheets + slack_maintenance
  1. path_inventory (item, quantity)
  2. confirm_inventory
  3. log_inventory_sheets + slack_inventory
  1. path_shift (role, reason)
  2. confirm_shift
  3. log_shift_sheets
  4. post_submit_menu (return to main menu OR end)
  1. fallback_node
  2. end_node

Results

~3 hrs/weekRequest handling time saved
Eliminated (instant Slack visibility)Response/logging delay
Reduced via guided menuMisrouted requests