Conversational AI | AI Apps | AI in Business | IVA | interface

Apps for providing solution for entire AI lifecycle

interface is a holistic solution with apps focusing on the crucial parts of an AI implementation and user journey and helps to integrate with popular enterprise app like CRM, ERP.

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Apps for every step

interface is a holistic solution to create and program an AI assistant through its entire lifecycle.

There are four stages primarily in the creation of an AI assistant, and there are apps catering to each stage.

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Academy

Build and train assistant

Academy App within the interface platform helps you create and manage the knowledge base that assistants leverage to converse with end users.

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Collaborative

For experience specialists and developers to build and train AI assistants for multiple channels and languages.

Pre-built Intelligence

Import existing packages from our package library for ready intelligence and domain understanding.

Always Learning

Easily add trigger phrases or training data by using our advanced text editor with Intellisense.

Customizable

Create using experience models to build and manage complex conversational flows to provide rich actionable responses to user queries.

Powerful Inference and Reasoning

Knowledge graphs are used for efficient data representation, retrieval, power inference, reasoning and recommendations.

Intuitive User Interface

Easily build and visualize using our intuitive user interface that helps build assistants fast.

Contextual FAQs

Define contextual FAQs with respect to entities, experiences, packages and Custom tags.

Developer Friendly

Code snippets that can be reused that are part of the packages such as business rules and validations that can be coded through the UI.

Collaborative

For experience specialists and developers to build and train AI assistants for multiple channels and languages.

Pre-built Intelligence

Import existing packages from our package library for ready intelligence and domain understanding.

Always Learning

Easily add trigger phrases or training data by using our advanced text editor with Intellisense.

Customizable

Create using experience models to build and manage complex conversational flows to provide rich actionable responses to user queries.

Powerful Inference and Reasoning

Knowledge graphs are used for efficient data representation, retrieval, power inference, reasoning and recommendations.

Intuitive User Interface

Easily build and visualize using our intuitive user interface that helps build assistants fast.

Contextual FAQs

Define contextual FAQs with respect to entities, experiences, packages and Custom tags.

Developer Friendly

Code snippets that can be reused that are part of the packages such as business rules and validations that can be coded through the UI.

Deploy and integrate assistant

Integrate with existing systems of record such as pre-built enterprise connectors to popular enterprise connectors to popular enterprise applications like CRM, ERP to deploy on premise or cloud.

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Advisory

Measure assistant's performance

Advisory App provides real time insights and dashboards on the assistant's performance to enable better decision making.

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Centralized Dashboard

Real-time data, visualizations and actionable insights for enterprises to continuously measure, analyze, and refine the assistant.

Real-time Actionable Insights

To make data-driven decisions for improving the performance of the AI assistant.

Conversational Analytics

For a deeper understanding of the customer behavior, popular intents, channel-specific usage and other business metrics.

Training Analytics

Get insights into training data performance and take targeted actions with Live tips on how to improve bot performance.

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A. P. T.

Refine with Assistant Performance Test

Assistant Performance Test (APT) helps you improve your assistant by continuous human assisted learning. Helps with annotation of conversations for improving assistant's performance.

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Clustering Queries

Learning models for clustering unmatched or unhandled queries based on closely matched experience to power efficient and faster training.

Machine Learning Models

To suggest new experiences to developers and append AI assistant functionality based on the user interest.

Test and Evaluate

After refining, run the regression test suite to ensure correctness and introduce new improved metrics.

Live Tagging

Include a Tagger in a conversation to help the Assistant with query understanding. Appending of training data on tagging unmatched queries.

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Agency

Switch to customer care

Agency App lets you switch to customer care by providing human assistance when required by the end users.

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Live Agent Support

To help connect to human agents for further assistance beyond the AI assistant.

Sentiment and Tone Aware

The Assistant can route conversations to Customer Support Agents.

Taggers

Allows developers to configure a Tagger in a live conversation and assist with query understanding.

Automatic Routing

After configuration, route to the right escalation channel based on various parameters and historical data.

Every interface that you are using can be better

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