Home AI and ML Cognitive Agent Assist IBM Cognitive Agent Assist
CAA is a natural language processing system based on deep learning. It is used as Virtual Agent for self-service, Agent Assist for call center agents and Knowledge Management system.
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Business Value

IBM Cognitive Agent Assist (CAA) is a natural language processing system based on deep learning. It supports SaaS & On-Premise deployment. On one hand, with efficient natural language processing technology, CAA system can understand the intentions of end users better. On another hand, it provides more comprehensive methods to retrieve useful information in the enterprise platform.

Key Features
Multiple tenant

management and orchestration of multiple chatbot

Different Conversation Services

Adoption of Watson Conversation service. on-premise conversation service, etc.

Knowledge Management

Knowledge Management for FAQ and unstructured data; Knowledge Graph based Open QA (question clarification, inquiry & reasoning)

Feedback

Feedback curation and analysis

Analytics & Reporting

Analytics & Reporting to understand user behavior

Integration

Integration framework with business systems

An automotive manufacturer

Problem

  • Answering a lot HR policy questions prevented HR staff from more valuable work
  • IT Helpdesk Call Center agents spent much time on the same questions repeatedly

Solution

  • HR Chatbot handles HR policy issues, integrated with HR system & WeChat
  • IT Helpdesk Chatbot integrated with IVR system supporting speech/text to text/speech and integrated with Ticketing system
  • Knowledge base constructed
A real estate group

Problem

  • High labor cost and repetitive work for HR to answer seriously homogeneous questions from enterprise employees 
  • Different HR policies in different regions, employees all over the country cannot get an accurate answer timely 

Solution

  • HR Chatbot integrated with multiple business systems, e-HR system and mobile application
  • Big Data Analysis provides salary consultancy service for HR personnel and managers
  • Knowledge Base constructed
A large mortgage service provider

Problem

  • Sub-optimal user experience caused by long waiting for agents to provide accurate answer
  • Much time for training new agents to get familiar with complicated processes and policies

Solution

  • Integrated the top routine complex procedures of the client into simplified interactive Dialogs and distinct intent 
  • Proactive insights and links to answers of questions
  • Complex dialog flows enable new agents to navigate through complex client queries quickly and easily