Build an AI‑Powered Game Support System with Alibaba Cloud SLS Smart Q&A Assistant

Background

Game support teams receive massive player complaints across five major scenarios: payment, item loss, matchmaking, anti‑cheat appeals, and social disputes. Investigating each issue traditionally requires 3–6 manual log queries across multiple SLS Logstores, leading to slow resolution, heavy reliance on expert knowledge, and backlog during peak periods.

Challenges

Slow investigation : Multi‑step cross‑store queries take minutes to tens of minutes per ticket.

Experience dependence : New agents struggle, and response quality varies.

Peak‑time backlog : Slow responses lower player satisfaction.

Solution Overview

The SLS Smart Q&A Assistant enables natural‑language queries over massive logs, automatically locating answers and generating draft replies. It compresses investigation time from minutes to seconds, identifies root causes for 13 predefined scenarios, and produces standardized responses based on SOP scripts.

Architecture

The system consists of a business knowledge base (SOP documents), an AI agent that queries logs, and integration points for messaging platforms. The overall architecture is illustrated below:

Step‑by‑Step Implementation

1. Create a Digital Employee

Navigate to the Alibaba Cloud Log Service console, locate the SOP Q&A Assistant, and create a new digital employee. Fill in basic information and link the knowledge base.

2. Prepare SOP Knowledge Base

Organize SOP documents that define the business scenarios and response scripts. An example SOP repository is available at

https://github.com/aliyun/sop-chat/blob/main/sop-docs-example/game-sop/sop-docs/SOP.md

.

3. Host SOP Repository in Codeup

Create a Git repository in Alibaba Cloud Codeup, push the local SOP directory, and note the enterprise ID, repository ID, and personal access token.

cd game-sop-docs
git init
git remote add origin [email protected]:619e222864fa260377314dee/game-sop-docs.git
git add .
git commit -m "init: add game SOP docs"
git push -u origin HEAD

4. Configure the Digital Employee

In the digital employee settings, add the Codeup repository information (enterprise ID, repo ID, token) so the assistant can retrieve the SOP content.

5. Integrate with DingTalk (or Feishu, WeChat Work)

Create a DingTalk robot via the DingTalk Open Platform, obtain the Client ID and Secret, and deploy the sop-chat-server from https://github.com/aliyun/sop-chat to bridge the assistant with DingTalk.

# Grant execution permission (macOS/Linux)
chmod +x sop-chat-server
# Start the server (generates default config.yaml on first run)
./sop-chat-server

Configure the AccessKeyId/AccessKeySecret in the UI, add the DingTalk channel, and test the connection.

6. Test the Assistant

Use the provided 13 test cases covering payment, item loss, matchmaking, anti‑cheat, and social disputes to verify that the assistant returns correct answers and draft replies.

1. 你好，我今天在微信充了 98 元礼包，微信那边已经扣款成功了，但游戏里钻石一直没到账，...

Conclusion

By ingesting game logs into SLS and enriching the assistant with a well‑structured SOP knowledge base, game operators can answer player issues instantly, dramatically improving response efficiency and service quality. The assistant’s coverage depends on the completeness of the SOP documents.