Smart Robot

AnBot 3.0 is an intelligent customer service robot based on the most advanced deep learning algorithms with high semantic understanding and deep self-learning abilities. It not only meets the needs of online customer service consulting, but also can handle all business online through connection with the business systems of various professional companies. Relying on accurate semantic understanding, it supports the portal integration and upgrade of front-end application functions in a comprehensive manner, thus greatly improving the online service experience for users.

Value Proposition

Deep Self-learning

AnBot covers all conversation log information of Ping An. In a data-driven mode, it can construct the knowledge base quickly with the smart recommendation schemes, thus reducing the online operation cost. Its knowledge base operation efficiency is 5 times higher than that of the last generation robot.

The Algorithm Determines the Core Abilities

AnBot has many core abilities such as inferring other information from one fact, smart error correction, long-sentence understanding, and multiple rounds of Q&A. At present, the accuracy of knowledge base retrieval based on deep semantic understanding has reached 96%. And in multiple-round dialogues, the entity recognition accuracy is over 95%.

Complete Man-machine Collaboration Solution

As the brain of the smart customer service of Ping An, AnBot can provide customers with a full set of smart customer service solutions. The non-inductive two-way switching between robot and the customer service rep, semantic understanding, emotion recognition and other services can be performed, with customer service efficiency doubled and the risk of complaints effectively controlled.

Central Control Robot

Used for bilateral or multilateral problems with unclear business attributes consulted by users. The central control robot, supported by powerful algorithms, can quickly clarify users’ intentions through questioning, thus realizing the one-stop online service experience for users.

Use Cases

Online Smart Air Ticket

Identify customer needs via extensive entity recognition, switching freely between tasks and Q&A.

Medical Guide

Via a unified service portal, the central control robot identifies the customers' intentions, and assigns the Q&A tasks to the corresponding department.

Comprehensive Financial Consultation

The unified service portal identifies customer needs and distributes them to corresponding business segments such as life insurance, property insurance, banking and securities through smart Q&A.

Success Stories

Ping An Bank

Functionality

Accurate Q&A

If a robot is not smart enough, it often fails to accurately recognize customers' problems, resulting in a poor customer experience and waste of efforts. AnBot, with the most advanced NLP algorithm, is capable of deep semantic understanding with high Q&A accuracy.
Context Understanding for Multi-round Dialogue

In response to scenarios where context semantics cannot be associated, man-machine dialogue is rigid and user expressions must adhere to the robots rules, AnBot is capable of context semantic analysis and supports multi-round Q&As, thus answering questions smoothly and naturally.
Smart Questioning Assisting Business Processing

For the weakness that users cannot be actively guided during online information collection and processing, smart questioning for service information can be achieved while entity extraction is performed, to connect the core business system for business processing.
Free Switching between Tasks and Q&A

For situations where robots cannot follow the changeable thinking of humans and cannot answer questions during processing, AnBot can switch between tasks and Q&A freely, such as answering questions whilst processing business instructions.
Deep Self-learning

Robots are unable to learn, so they need manual knowledge maintenance, which results in cumbersome efforts, frequent missed instructions and high knowledge base maintenance costs. Deep self-learning, together with manual assisting confirmation, can significantly reduce labor costs.
Central Control Robot

When one service portal undertakes multiple business lines with a robot maintained separately for each, multiple robots cannot cooperate. The central control robot can identify the customers' intentions and assigns Q&A tasks to the robot in the corresponding business field.