Ticketing Solution Overview

Note: This is an early preview version. Features are still being improved and we are continuously working on enhancements. Feedback is welcome!

1. Background (Why)

Industry/Role/Management Problems Solved

Enterprises face various types of service requests in daily operations: equipment repairs, IT support, customer complaints, consultations, etc. These requests come from scattered sources (CRM systems, field engineers, emails, public forms, etc.), have different processing workflows, and lack unified tracking and management mechanisms.

Typical Business Scenarios:

• Equipment Repair: After-sales team handles equipment repair requests, needs to record device-specific information like serial numbers, fault codes, spare parts
• IT Support: IT department handles internal employee requests for password resets, software installations, network issues
• Customer Complaints: Customer service team handles multi-channel complaints, some emotionally charged customers need priority handling
• Customer Self-Service: End customers want to conveniently submit service requests and track processing progress

Target User Profile

Pain Points of Current Mainstream Solutions

• High Cost / Slow Customization: SaaS ticketing systems are expensive, custom development cycles are long
• System Fragmentation, Data Silos: Business data scattered across different systems, difficult to unify analysis and decision-making
• Fast Business Changes, Hard to Evolve: When business requirements change, systems are difficult to adjust quickly
• Slow Service Response: Requests flowing between different systems cannot be dispatched promptly
• Opaque Process: Customers cannot track ticket progress, frequent inquiries increase customer service pressure
• Quality Difficult to Guarantee: Lack of SLA monitoring, timeouts and negative feedback cannot be alerted in time

2. Product Benchmarking (Benchmark)

Mainstream Products in the Market

• SaaS: Salesforce, Zendesk, Odoo, etc.
• Custom Systems / Internal Systems

Benchmarking Dimensions

• Feature Coverage
• Flexibility
• Extensibility
• AI Usage Approach

NocoBase Solution Differentiators

Platform-level Advantages:

• Configuration-First: From underlying data tables to business types, SLA, skill routing - all managed through configuration
• Low-Code Rapid Development: Faster than custom development, more flexible than SaaS

What Traditional Systems Cannot Do or Cost Too Much:

• AI-Native Integration: Leveraging NocoBase's AI plugins for intelligent classification, form assistance, knowledge recommendations
• All Designs Can Be Replicated by Users: Users can extend based on templates
• T-Shaped Data Architecture: Main table + business extension tables, adding new business types only requires adding extension tables

3. Design Principles

• Low Cognitive Cost
• Business Before Technology
• Evolvable, Not One-Time Completion
• Configuration First, Code as Fallback
• Human-AI Collaboration, Not AI Replacing Humans
• All Designs Should Be Replicable by Users

4. Solution Overview

Summary Introduction

A universal ticketing platform built on NocoBase low-code platform, achieving:

• Unified Entry: Multi-source integration, standardized processing
• Intelligent Distribution: AI-assisted classification, load-balanced assignment
• Polymorphic Business: Core main table + business extension tables, flexible extension
• Closed-Loop Feedback: SLA monitoring, customer ratings, negative feedback follow-up

Ticket Processing Flow

Multi-Source Input → Pre-processing/AI Analysis → Intelligent Assignment → Manual Execution → Feedback Loop
      ↓                      ↓                          ↓                    ↓                ↓
 Dedup Check           Intent Recognition          Skill Matching      Status Flow      Satisfaction Rating
                       Sentiment Analysis          Load Balancing      SLA Monitoring   Negative Feedback Follow-up
                       Auto Reply                  Queue Management    Comment Communication  Data Archiving

Core Module List

Core Interface Display

5. AI Employees

AI Employee Types and Scenarios

• Customer Service Assistant, Sales Assistant, Data Analyst, Auditor
• Assisting humans, not replacing them

AI Employee Value Quantification

In this solution, AI employees can:

6. Highlights

1. T-Shaped Data Architecture

• All tickets share the main table with unified flow logic
• Business extension tables carry type-specific fields, flexible extension
• Adding new business types only requires adding extension tables, without affecting the main flow

2. Complete Ticket Lifecycle

• New → Assigned → Processing → Pending → Resolved → Closed
• Supports complex scenarios like transfer, return, reopen
• SLA timing accurate to pending pause

3. Multi-Channel Unified Integration

• Public forms, customer portal, API, email, agent-created
• Idempotency check prevents duplicate creation

4. AI-Native Integration

• Not "adding an AI button", but integrated into every step
• Intent recognition, sentiment analysis, knowledge recommendation, reply polishing

7. Installation & Deployment

How to Install and Use

Use migration management to migrate and integrate various partial applications into other applications.

8. Roadmap (Continuously Updated)

• System Embedding: Support embedding the ticketing module into various business systems like ERP, CRM, etc.
• Ticket Interconnection: Upstream/downstream system ticket integration and status callbacks for cross-system ticket collaboration
• AI Automation: AI employees embedded in workflows, supporting background auto-execution for unattended processing
• Multi-Tenancy: Horizontal scaling via multi-space/multi-app architecture, enabling distribution to different service teams for independent operation
• Knowledge Base RAG: Automatic vectorization of all data (tickets, customers, products, etc.) for intelligent retrieval and knowledge recommendations
• Multi-Language Support: Interface and content support for multiple languages, enabling cross-border/cross-regional team collaboration