Deep - learning to mimic human behaviour

A unique communication platform that assists customers to resolve their queries or support requests at point of contact through Web, App or WhatsApp. Uses advanced pre-trained neural network algorithms to process multiple queries simultaneously, and assist in quick closure of tickets by the customer

Uncapp-able

Superior, human-like cognitive capabilities that allow it to read text, images as well as documents, creating a super-efficient system for interacting with customers.

Patent pending feature that enables resolution of multiple intents simultaneously.

Auto complete feature simplifies customer experience journey, prompting him with the exact suggestion of what he is looking for Intelligent UI and design that allows the customer to change request type by himself.

Can function as a virtual sales assistant, upselling and cross-selling products, across the board

Intent-reader

Can identify customer intent with high degree of accuracy and handle complex business problems with ease.
Assists the customer in resolving most of his support queries at the point of contact, with minimal human intervention.
Request soft copy of documents.
Register a claim.
Request for claim status.
Change name / address or other account related information.
Process Information

Acu- men-tal

Its objective is to reduce ticket generation by 80% Intelligent built in analytics with deep learning enables personalized promotions and intelligent cross sell / upsell of products based on customer profile and user behavior / nature of query.

Advantages

There are 6 ways in which Assisted Closure offers functional
superiority and distinct advantages to its users:

Easy to train

Multiple Query Resolution

Memory-Enabled

Virtual Salesman

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Cost-Saver

⇒

Time-Saver

∞

The future of chatbots

Feature	Assisted Closure	Chatbot
Multiple Intents	Yes	No
Understanding long unstructured text	Yes	No
Use email data for training	Ample training data with high launch accuracy	Less data for training Lower launch accuracy High learning curve for ML with trial and error
Memory of past tickets (Open & Closed)	Yes	No
Advertisements, campaigns, cross sell / upsell products, marketing material featured between tickets, Banners	Yes	No
App within App: Not restricted to boundaries / limitations of query / service bot	Yes	No
Throw / push notifications / sales promotions through or within app	Yes	No
Query resolution	Complete process flow for each query or ticket	2 way chat conversation / decision tree based IVR
Autocomplete	Autofill (60% time conservation)	Dropdown
Model	Deep Learning Pattern recognition	NLP + Decision Tree Keyword based