Aijia Customer Service Documentation
Product documentation for Aijia Customer Service, the AI-native support operations system for private-domain, WeCom, ecommerce, social, messaging, and enterprise service operations.
What Aijia Customer Service Is
Aijia Customer Service is an AI-native support operations system for private-domain operations, WeCom customer groups, ecommerce, social, messaging, and multi-team service organizations.
It combines:
- customer identity and business conversations for customer, contact, prior commitment, multi-channel context, and active service case;
- knowledge operations for product, service rules, material lists, campaign, and brand policies;
- private-domain collaboration and back-office verification across customer groups, internal teams, fulfillment partners, actual executors, and verified back-office information;
- human review for public group replies, sensitive messages, risky commitments, and uncertain cases;
- evidence trail for original messages, customer-facing wording, review, delivery results, completion feedback, and key materials.
The goal is not unlimited automation. The goal is governed enterprise support operations.
Core Concepts
Support Operations Layer
Customer messages, identity, service cases, knowledge, execution permissions, review rules, and evidence are managed in one operating layer. This prevents the team from scattering decisions across disconnected inboxes, spreadsheets, customer groups, and back offices.
Customer Identity and Business Conversations
Customer identity identifies the customer, contact, organization, prior commitments, and multi-channel touchpoints. Business conversations attach messages, participants, waiting states, and evidence to one service context.
Service Cases and Waiting States
A service case is the current customer issue. Waiting state records who is waiting for whom, what is missing, who moves next, and whether the customer or partner has completed the action.
AI
The AI reads the customer request, combines customer identity, business context, and approved knowledge, identifies risk, and proposes a customer-safe reply or handling suggestion. It should be treated as an assistant inside a controlled workflow, not as an unchecked decision maker.
Authorized Back-Office Actions
Authorized back-office actions help teams read approved work context, prepare actions, confirm low-risk steps, and capture evidence when configured to do so.
Human Review
Review mode is used for refund commitments, compensation, public group-sensitive messages, partner relays, uncertain customer identity, and uncertain cases. Humans keep final control where risk is high.
Evidence Trail
Important actions should be inspectable after they happen: what the customer said, what AI suggested, who reviewed it, what was sent to the customer, how waiting state changed, and whether completion feedback plus evidence are complete.
Recommended Reading Order
- Quick Start
- AI Agent Commercial Delivery Rollout Blueprint
- Service Case and Waiting State Playbook
- Partner Fulfillment Collaboration Playbook
- Authorized Back-Office Actions Overview
- Knowledge Operations
- Knowledge Quality and Release Checklist
- Human Review and Risk Control
- Sales Conversion Support Playbook
- Multilingual Support Rollout Playbook
- AI Support Quality Review Playbook
- Evidence Trail and Dispute Handling Playbook
- Platform Change Response Playbook
- Social Commerce Support Playbook
- Private-Domain Support Playbook
- WeCom Collaboration Support Playbook
- Private-Domain AI-Native Service Operations Blueprint
- Private-Domain + Enterprise AI Support Rollout Playbook
- After-Sales Execution Playbook
- Rollout Metrics and Pilot Plan
- AI Support Evaluation Checklist
- Execution Governance
- Security and Platform Boundaries
Where Aijia Customer Service Fits
Aijia Customer Service is useful when:
- support spans private-domain, ecommerce, social media, messaging, and enterprise back offices;
- WeCom customer groups, internal teams, fulfillment partners, and actual executors need to move service cases forward;
- the team needs to manage customer identity, business conversations, and waiting states;
- platform-provided capabilities do not cover every back-office action;
- product, logistics, refund, and brand policies change often;
- managers need human review and an evidence trail;
- one team manages multiple stores, regions, brands, or clients.
It is not designed to bypass platform controls or replace all human judgment. It is designed to make support operations faster, more consistent, and more auditable.
