TPIsoftware｜SysTalk.Chat｜AI Conversational Service

AI Brain for Enterprise Customer Service Chatbot

π-Type Smart Customer Service

Accurate Algorithm, Comprehensive Management, Reliable Implementation

Featuring pioneering algorithms, maintenance tools and comprehensive management, SysTalk.Chat provides a π-type smart customer service with high accuracy, delivering a smart, human-like conversational AI service.

Maintenance Tools Optimize Recognition

SysTalk.Chat provides brain optimization tools and standard steps, such as corpus-based unknown word classification, intent conflict detection, identification of model accuracy and more, facilitating AI brain training.

Comprehensive Application Management

With 5 feature highlights of text chat human agent platform, management reports, service management, access management and project management, self-maintenance management can be achieved with ease.

Outstanding Accuracy + Tailored Algorithms

Combined with Google BERT and exclusive SysTalk algorithms, SysTalk.Chat can better grasp user intent and achieve high accuracy, delivering an engaging NLU conversational service.

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Core Modules：
Dual brain + single process architecture: core module operating mode

FLOW

Connect the dual brains and the system APIs to create a conversation flow with "multi-round dialogue" and "multi-turn dialogue" designs, bringing a human-like conversation experience.

Human-Like Conversation Design

Multi-Round Dialogue

improve service completion rate

Retain information + ask follow-up questions for clarification and more information to handle vague responses

Multi-Turn

Reduce bounce rate

Memorize earlier conversations + switch between different flows when the topic changes so that the same conversation won't start over again

Smart

Increase first-time resolution rate

Fast

Improve service efficiency

Scalable

Scale your project scope

FAQ

The lightweight FAQ manages general queries with fixed responses, providing proper and accurate answers to varying questions in real time.

Create hierarchical conversations

Simulate human conversations
to reduce conversation fragmentation

The right answer to multiple questions

Finding the right answer,
regardless of the way customers ask the question.

Mark synonyms and disable words

Enhanced synonymy database
to improve response rate.

Two-step Comparsion

Step #1

Massive data scoring

FAQ can quickly compare massive data and remove low to medium correlations. Low computing power.

Questions received

Step #2

Specific data comparsion

6 different algorithms filter the data and give a precise scoring.

NLU

NLU manages contextual questions and requests through "intent classification" and "entity recognition, performing human-like understanding of user needs and key information.

Personalized Services

Intent Classification

Identifying service type

Entity Recognition

Extracting key information

NLU Brain Engine

I want to pay my credit card bill!

Using the N-Gram model, each conversation is decomposed and vectorized to obtain feature value results. The feature value is used as a base value for vector space positioning.