Natural language processing (NLP) enables human-to-machine communication without humans having to learn or speak programming languages. Put simply, if you've ever used google search engine or GPS navigation system ever, you’ve already interacted with an NLP models system. Natural language processing has a key role in the matrix of automation. Being one of the most fascinating components of AI, NLP has colossal potential to transform the way we communicate.
What makes Engagely’s NLP engine stand out from others
Context Driven Conversations
Context is the soul of the conversation. It helps to save and share the parameters across the whole session. Engagely’s NLP engine allows the IVA (Intelligent virtual assistant) to handle all context switching with ease and efficiency. Thereby allowing users to easily switch between multiple conversations without having to repeat the query.
Superior Sentiment-apt Responses
Emotions play a vital role in communication and so does intelligent sentiment analysis. It takes over and interprets words like happy, great as emotions that helps understand customer preferences, empathize with them and craft responses accordingly.
Dialogue Management
Dialog Management System (DMS) is the component that facilitates interpretation and contextualisation of human-like conversations between bots and customers. Based on the user input, the NLP leverages conversational context and dialog logic components to drive out of box conversational experiences.
Seamless Interruption Handling
Users do not always follow the defined conversational flow. They may interrupt the flow with a question, however, Engagely is functioned to seamlessly handle the interruptions without breaking the flow.
Natural Conversations Across Languages
Speak your `customer’s language irrespective of ambiguities, language grammar, translation issues, spelling mistakes, dialects and accents. With the multilingual capability, Engagely caters to diverse clientele over a variety of modern enterprise channels in 120+ global languages.
‘Self-improvement On Job’ Model
The NLP engine gets better with each interaction, even from the ones that were flagged as unhandled. Engagely’s NLP engine is designed to learn from every new conversation and thus improve itself autonomously through practice & over the time.
Industry Specific Models
From BFSI to healthcare to retail and telecom, the leading NLP model understands industry-specific lingo across various verticals and has already transformed a number of industries. It combines technology and human languages to improve a multitude of industries and their products, solutions, and services.
How natural language processing (NLP) technology works
- Utterance- An utterance is simply anything a user says. It is the user input or the phrases typed or said by the user when they refer to a specific intent are looking for a solution to a particular query.
- Intent- Intent is the task the user wants to accomplish. The pre-trained Natural Language Processing (NLP)breaks down the input message into smaller parts and accurately understands the multiple intents even in the most complex queries and provides the most accurate response.
- Entity- Entities include the specific details needed for identifying the user’s intent. The NLP engine further extracts key information to understand the user input, or simply uses it to extract important information to store in the database.
- The FM-ML Statistical Model- The amalgamation of Machine Learning (ML), Fundamental Meaning (FM) engine and Knowledge Graph helps evaluate the accurate intents in the user utterances and drive the context specific conversations efficiently.
