Conversational AI

Conversational AI combines data, machine learning (ML), and natural language processing (NLP)

What are Conversational AI Chatbots?

Conversational AI combines data, machine learning (ML), and natural language processing (NLP) to create technologies that understands intent, analyzes different languages and contexts, and imitates human conversation. This empowers technologies like chatbots, virtual assistants, or virtual agents to learn and become more intelligent over time, and quickly and efficiently communicate in a human-like manner via text and speech.

There are two main components of Conversational AI:

Machine Learning (ML)

Based on the idea that systems can continually learn and identify patterns through repeated use and automatically improve themselves with minimal human interaction.

Natural Language Processing (NLP)

Technologies that enable computers to understand language in speech or text including intent and sentiment.

How Conversational AI works?

conversational ai workflow

Why Conversational AI Chatbots?

chatbot on phone

Traditional chatbots follow simple pre-defined rules without a true understanding of intent and context. Although some may claim to have conversational abilities, these chatbots are typically text-based and are trained to respond to certain keywords for every foreseeable scenario. As a result, if questions are off script, they may be ineffective at answering them. 

Conversational AI chatbots, conversational AI assistants or AI chatbots are built upon layers of complex systems that enable continuous self-improvement – becoming more intelligent and mature as they learn with conversation data and supervised machine learning. In addition, using natural language processing (NLP), AI chatbots emulate human conversations by analyzing and understanding sentiment and context in different languages.

NeuroSoph’s Specto AI platform builds custom-tailored conversational AI chatbots that are trained with your industry-specific data and can augment any customer interaction, improve productivity, and resolve requests faster than ever in your organization.

Benefits of Conversational AI Chatbots

Some benefits from leveraging conversational AI chatbots include:


Text & Voice

Text, voice and outbound interactions



Highest standard of security and compliance


Brand Experience

Differentiated brand experience with personalized responses and guidance


Cost Effective

Reducing cost of customer care by reducing volume of inquiries to select channels



Omnichannel for more customer engagement and accessible 24/7 365 days



Instant customer feedback and actionable insights to inform future developments


Optimizing Workforce

Optimizing workforce with decreased workload and creating more time for human agents to solve the most complex problems



Higher productivity with task and process automation and automated conversation routing


Customer Satisfaction

Higher customer satisfaction with seamless user experience, intuitive self-service, faster resolution and more meaningful engagements

By enabling conversational AI chatbots to learn and improve, the value of AI chatbot solutions will increase over time. As a result, many different organizations are increasingly incorporating intelligent chatbot solutions to optimize their workforce, so they can be more productive and focus on more complex tasks while resolving requests faster than ever.

Traditional Chatbots vs. Conversational AI Chatbots

Conversational AI Chatbots

Understands & responds to both text and voice

Multiple channels – blogs, websites, voice assistance, call centres, etc.

Understands context, sentiment, intent of a conversations & in different languages

Learns from interactions & improves over time with supervised machine learning

Handles wide-scope & non- linear interactions - out of scope topics & topic changes

Enterprise-ready, integrates with existing data sources & can be bootstrapped to learn new information

Can integrate with 3rd party systems (e.g. RPA, ERP, CRM, etc.) to perform tasks


Text & Voice


Natural Language Understanding

Continual Learning

Dynamic Interactions

3rd party integrations


Traditional Chatbots

Understands & responds in text only

Single channel - chat

Keyword driven, pre-determined & rule-based dialogue flow

Has to be reconfigured, updated & revised with new rules

Rule-based interactions - cannot handle out of scope interactions

Manual maintenance and training on every scenario make it difficult and time consuming to scale

Basic functionality may limit integration with existing infrastructure

Contact NeuroSoph