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Twig AIv1.2

Customer support

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5.0(2)

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AI analyzes docs to answer customer questions

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Overview Discussion

Overview

Twig AI Agents are able to perform action that the typical AI Support Engineer performs. Including answering QnA, Looking up user data, Taking Actions, Making API calls etc.

Twig support several interfaces including web, InApp Integrations, Browser Integrations and ticketing tool integrations into ZenDesk, HelpScout.

Twig is an AI-powered tool designed to help users quickly and easily find the answers they need from technical documentation without having to spend hours sifting through endless pages of documents. The tool works by semantically analyzing documentation, knowledge bases, past support tickets, and other data sources to provide accurate responses to customers' complex questions. This significantly reduces the costs of customer support by up to 30%. Twig's AI models are trained on publicly available data, allowing it to find and recommend relevant responses to user questions with confidence. The recommended responses include citations that increase the trustworthiness of the response by showing users where to find additional information. Twig also helps support agents become more productive by automating tedious tasks and providing powerful tools that replace busy work with human empathy. It enables agents to improve the quality of customer engagement by bringing higher minimum standards on response quality and helping them notice potential risks in responses. Twig can integrate with most popular documentation and knowledge base products, and it sanitizes data, removing any personally identifiable information (PII) to ensure privacy protection. Twig is an AI tool designed to significantly enhance the customer experience by providing accurate, relevant, and speedy responses to technical questions.

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Twig AIv1.2

Twig AIInitial

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Twig AI v1.2

Jan 3, 2025

Chandan Maruthi

wrote:

Twig launches AI agents for B2B Customer Support. Twig's Agent factory allows customers to create and launch powerful AI agents for the users. These Agents can lookup user specific information, make API calls and take actions. In addition to a sophisticated AI QnA platform with automated evaluations.

Initial release

June 25, 2022

Chandan Maruthi

wrote:

Initial release of Twig AI.

Chandan Maruthi

@chandanmaruthi

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Pros and Cons

Pros

Fast, accurate technical support

Saves time finding documentation

Semantically analyzes data

Reduces customer support costs

Trains on public data

Recommends relevant user answers

Includes answer citations

Automates tedious tasks

Enhances agent productivity

Sets high response standards

Identifies response risks

Integrates with popular products

Sanitizes data for privacy

Speedy response to questions

Recommended responses increase trust

Improves customer engagement quality

Documentation and knowledge base integration

Daily data refreshes

Understanding document-specific structure

Links back to source

Sentiment analysis for risks

Improved support agent tools

View 17 more pros

Cons

Relies on Public Data

Dependent on Integrated Products

No Sentiment Analysis

Lacks Custom Training Data

No Mention of Multilingual Support

No Offline Capabilities

Lacking Advanced Analytics

Dependent on Quality of Documentations

No API Mentioned

No Autonomous Learning Feature

View 5 more cons

Q&A

What is Twig AI?

Twig AI is an Artificial Intelligence powered tool that specializes in delivering accurate and fast technical support through a chatbot. It is designed to provide quick and appropriate answers to users directly from technical documentation.

What does Twig AI do?

Twig AI semantically analyzes technical documentation, knowledge bases, and past support tickets to provide accurate responses to complex customer queries. It integrates with popular documentation and knowledge base products to direct customers to relevant answers, thereby reducing the time and cost of customer support.

How does Twig AI answer complex customer support questions?

Twig AI uses AI models to semantically analyze technical documentation, past support tickets and other data sources. These models are trained on publicly available data to identify and provide the most relevant answers to users' complex queries.

What technologies does Twig AI use to deliver its services?

Twig AI employs advanced AI models that are trained on publicly available data. It uses semantic analysis technology to read and comprehend technical documentation, knowledge bases, and past support tickets. In addition, Twig AI uses sentiment analysis to help agents notice potential risks in responses.

How does Twig AI reduce customer support costs?

Twig AI reduces customer support costs by automating tasks that would typically require human involvement. This automation also leads to more accurate response selection, reducing the necessity for further interaction and thus lowering the costs by around 30%.

How is Twig AI trained to recognize and respond to questions?

Twig AI's models are trained on publicly available data. This training allows the AI to recognize various types of queries and accurately determine the most relevant responses from the analyzed documentation, knowledge bases, and past support tickets.

+ Show 13 more

What kind of data does Twig AI analyze?

Twig AI analyzes technical documentation, past support tickets, and knowledge bases. It ingests this data through its pipelines that integrate with most popular documentation and knowledge base products.

How does Twig AI ensure the privacy and protection of user data?

Twig AI ensures the privacy and protection of user data by sanitizing the collected information, removing all personally identifiable information (PII). This process of PII anonymization guarantees that all the processed data is privacy-safe.

How does Twig AI improve support agent productivity?

Twig AI improves support agent productivity by automating repeatable tasks and equipping the agents with powerful tools that replace busy work with human empathy. These tools also set higher minimum standards for response quality and help agents identify possible risks in responses.

What platforms or tools can Twig AI integrate with?

Twig AI is compatible with most popular documentation and knowledge base products, drawing from these various sources to provide comprehensive support responses.

How does Twig AI improve the quality of customer engagement?

Twig AI improves the quality of customer engagement by bringing higher minimum standards on response quality. It also helps agents notice potential risks in responses, ensuring that responses are both accurate and sensitive to the customer’s situation.

What is Twig AI's mechanism for sentiment analysis?

Twig AI employs sentiment analysis as a strategy for maintaining high-quality customer engagement. It alerts support agents to potential risks in the sentiment of their responses, allowing them to adjust and optimize the response to suit the customer's mood and need.

What productivity tools does Twig AI offer for support agents?

Twig AI provides support agents with tools that accelerate and improve the quality of customer engagement. These include AI recommendations for responses, sentiment analytics for monitoring potential risks in agent responses, and automated refreshing of data which replaces busy work with tasks requiring human empathy.

What are the advantages of using Twig AI?

Using Twig AI affords many advantages, including reducing customer support costs by approximately 30%, improving support agent productivity by automating busy work, enhancing response quality, and protecting user data privacy with PII anonymization.

What is Twig AI's approach to analyzing and understanding technical documentation?

Twig AI employs semantic analysis to understand technical documentation. It scans the structure and content of documents, enabling it to grasp the crucial details and deliver relevant responses to customer queries.

How does Twig AI deal with personal identifiable information in the data it processes?

Twig AI ensures the privacy of Personal Identifiable Information (PII) by implementing an anonymization process. This sanitization removes all PII from the data, ensuring data protection standards are adhered to.

How does Twig AI select the most relevant responses to user's questions?

Twig AI uses AI models trained on publicly available data to analyze user's questions and find the most relevant responses. It goes over the documentation, knowledge bases, and past support tickets, semantically analyzing the context of the text to find the best answers.

How does Twig AI help to improve response quality?

Twig AI improves response quality by basing its responses on semantic analysis of technical documentation, past support tickets, and knowledge bases. It also maintains a high minimum standard for responses and uses AI to alert agents of potential response risks.

How does Twig AI's citation feature work?

The citation feature in Twig AI provides references for each recommended response. These citations show users where to find additional information, increasing the trustworthiness and veracity of the responses by tracing them back to the original sources.

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Twig AIv1.2

Overview