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PLATFORM /
VIRTUAL AGENT (NLP)

Drive Intent-based Conversations in customer’s preferred languages

Understand Customers’ Intent, Turn Interactions into structured data and Automate Support with domain-specified NLP Model. Enable end-to-end fulfilment

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Redefine Customer Conversations With Maximum Accuracy & Performance

Solution Built-in with machine learning algorithm that Accelerates Human-like Interactions

Natural Language Generation

Orchestrate multiple actions with the innovation of sentence generation based on emotions, multiple languages and users’ intent. The virtual agent entitles to documents & labels them based on keywords & phrases.

Pre-built Domain

Reduce the time of training your virtual agent where Twixor is powered with specific domain NLP that can be customized based on business needs and industry.

Gain Accuracy Over time

Reap business benefits and accuracy from the day of implementation. Equipped with Model-testing capability that ensures to get smarter and better after every practical knowledge resource & conversation.

Solution Built-in with machine learning algorithm that Accelerates Human-like Interactions

Twixor’s Virtual Agent consists of a machine learning model that combines domain taxonomy, a semantic rules-driven model, and Natural Language Understanding (.
The combination helps to understand users’ intent, emotions, complex human conversations, and responses with the highest degree of accuracy.
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Utterance

Understands Every Statement & Expression

Our Virtual Agent is built in a way that can understand and refer to whatever the user says. The Virtual Assistant can refer to any sentence organized in multiple languages in any logical order simultaneously. The VA can respond to overall requests from users in real-time.

  • Smart Assistant
  • Positive & Negative Data
  • Refers Overlapping Intents
Entity Extraction

Defines Data, Time & Locations Based on Intents

The platform identifies key elements processed by the user, such as addresses, restaurant names, payment, and other complex logic. These elements can be categorized based on users’ previous conversations. A pre-built common entity recognition engine powers Twixor’s Virtual Agent to save your valuable time on training.

  • Identifies Unstructured Text
  • Recognizes Date/time, Percentage
  • Pre-built Recognization Engine
Intent Builder

Customize & Discover Intent From Resources, Chat Records

Integrate a diversified intent from resources or build your own intent based on domain-specific conversations. Twixor’s Virtual Agent platform comes with an insightful intent builder ecosystem designed for conditional branching, managing interruptions, and supporting third-party intents. The pre-built intent can be reused or customized based on journey needs.

  • Pre-built Intent Recognition
  • Third-party Resources
  • Reduces Virtual Agent Training
Powerful Analytics

Keep Track of Each Tickets & Agent Performance In-hand

Measure the performance of your agents and bot by analyizing key metrics like conversations per day, first response time, Average chat time, and resolutions in real-time. With the help of insightful data, extract agent productivity reports, chat flow and conversation-based reports for better decision making.

  • Connect with Other Analytical Solutions
  • Data Visualization
  • Export to Analytical Tools

Bring Personalized Conversations Into Reality With the Power of Virtual Agents

With NLP Approach, take conversations more personalized, human-centric and accurate

Faster time-to-value

Multilingual Support

AI Recommendations

Improve Support Agility

Improve Resolution Rate

No-code Integration

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Transform Customer Experience, Reduce Resolution time & Build Meaningful Conversations with

Intelligent Virtual Agent

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