Examples of applications fueled by our high-volume, high-accuracy AI Data:

  1. Conversational Intelligent Platforms, Virtual Assistants, Sentiment Based Routing.

    More than a Bot! To build a cognitive solution that handles all forms of simple to complex interactions (automating FAQ’s, collecting feedback, routing conversations based on customer sentiment, paying bills, appointments, etc.) you require large amounts of audio and text data. The more AI training data, the better it responds to user queries.

    Our technology and methodology allow us to collect your customer phone interactions and provide you the high-volume, high-accuracy data to train your Conversational Intelligent Platforms, Virtual Assistant.

  2. AI Chatbots – Basic to Advanced Intelligent Bots

    Understanding customer intent and responding correctly. AI chatbots have various levels, with a starting point of the text-to-text match and using a probabilistic matching framework. As the data becomes richer, conversational maturity levels can be further improvised.

    Conversations can be classified as two types: 1) Short conversations, where key words are used as intent with further mapping to a specific response. 2) Long conversations, where a context-building exercise such as a topic model is used, in which a topic is a context and context-to-response mapping is required.

    We provide organizations with rich, labeled training data for any maturity level of Conversational AI initiatives:

    Level 1 – Basic Chat Bot

    • Mapping of receiver text with sender text

    • Conversation’s platform: dialog flow, questions and answers are mapped (1st level), based on regular expressions and overlap percentage with the query

    Level 2 – More than a Bot — Intelligent Dialog Management

    • Abstract layers are framed for intent identification

    • ML models are trained to predict intent

    • Intent mapping and response are configured

    Level 3 – Generative Intelligence — Advanced Mechanism to Predict Intents

    • Context creation

    • Context training using deep learning models

    • Context prediction for the text sent by the sender

    • Response mapping and display the response to the end user

  3. AI Analytics –
    Gain better insights into call data, thereby improving your customer experience and operational efficiency. Our custom labeled and tailored call and text data is ready to be used by both AI and Analytics teams.