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SK Telecom · Apr 2025 – Oct 2025

A-dot Scheduling Agent

Role · Agent design and development

2.5×schedule MAU growth203K → 511K (Jan → Sep 2025)
67%registrations via agent66K of 98K schedule registrations

01Background & Goals

  • We built an agent that handles A-dot's events and reminders through conversation.
  • The goal was to handle multi-intent requests such as "add a dentist appointment at 3 tomorrow and push Friday's meeting back 30 minutes" quickly and accurately.

02Key Challenges

  • C1 Multi-intent requests and response latency
  • C2 Integration with external calendars (Outlook, Google Calendar) and subscription calendars
  • C3 Accurate handling of time information such as recurring events and reminders

03Contributions

Agent architecture with the Plan-and-Execute pattern and a Refine stepC1
  1. Plan: splits the request into sub-tasks and orders them
  2. Execute (sequential): completes dependent sub-tasks in order
  3. Execute (parallel): runs independent sub-tasks in parallel to cut latency
  4. Refine: re-plans from the execution results to raise task accuracy
External and subscription calendar integrationC2
  1. Designed the flow so the LLM distinguishes external calendars (Outlook, Google Calendar) from subscription calendars (benefit and event schedules) and decides whether each is linked and can be read, changed or deleted
RAG for schedule retrievalC1
  1. Filtering: narrows candidate events by owner, subscription and date range
  2. Parallel search: splits candidates into N chunks and calls the LLM in parallel to find the requested events within the latency budget
  3. Verification: checks that each extracted event matches the request and extracts the supporting evidence to improve accuracy
Prompt engineering for time informationC3
  1. Designed prompts that use the iCalendar standard and ISO 8601 durations so recurring events and reminders are handled precisely

04Tech Stack

Framework / Platform
LangGraph, Gradio, FastAPI
Methodology
Prompt engineering, RAG, Plan-and-Execute

05Results

  • 67% of schedule registrations came through the agent (66K of 98K)
  • Service-wide schedule MAU grew 2.5× (203K in Jan → 511K in Sep 2025)

06Reference Material