Case Studies Building a better chatbot with text annotation services

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	Building a better chatbot with text annotation services

Building a better chatbot with text annotation services

Technology Category	Analytics & Modeling - Machine Learning Analytics & Modeling - Natural Language Processing (NLP)
Applicable Industries	Professional Service Retail
Applicable Functions	Business Operation Sales & Marketing
Use Cases	Chatbots
Services	Data Science Services System Integration
Challenge	Chatbots often face limitations in answering diverse questions or managing various tasks, leading to rigid and frustrating user experiences. True Lark aimed to overcome these limitations by focusing on specific industries to provide a full range of necessary context. However, to achieve this, they needed labeled data to build their models, which required extensive time and effort. True Lark's internal team was unable to dedicate the necessary time to data annotation without neglecting other critical aspects of product development. This led them to seek external assistance from CloudFactory for data labeling operations. Read More
About Customer	True Lark is an AI communications platform that offers a virtual business assistant named Sasha, designed to handle customer inquiries, book appointments, and make purchases around the clock. The company primarily serves personal service businesses such as dental offices, spas, and exercise studios, which require efficient customer engagement and lead management. Founded by Srivatsan Laxman, True Lark leverages AI to address the unmet potential in the personal service sector, providing automated conversational experiences that enhance customer service and operational efficiency. CloudFactory supports True Lark by annotating large volumes of customer conversations, enabling the company to focus on AI model innovation and rapid productization. Read More
Solution	True Lark partnered with CloudFactory to handle the data annotation tasks required for training their AI models. CloudFactory's team was trained to understand the nuances of language necessary for accurate text tagging. True Lark initially spent time explaining the requirements to CloudFactory, which then took over the process of reviewing and labeling large batches of text message conversations. The annotations included identifying nouns, appointment times, staff members, and service types, as well as determining the nature of client requests. This collaboration allowed True Lark to focus on testing and training their AI models, leading to significant improvements in their virtual assistant, Sasha. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Machine Learning

Analytics & Modeling - Natural Language Processing (NLP)

Applicable Industries

Professional Service

Retail

Applicable Functions

Business Operation

Sales & Marketing

Use Cases

Chatbots

Services

Data Science Services

System Integration

Challenge

Chatbots often face limitations in answering diverse questions or managing various tasks, leading to rigid and frustrating user experiences. True Lark aimed to overcome these limitations by focusing on specific industries to provide a full range of necessary context. However, to achieve this, they needed labeled data to build their models, which required extensive time and effort. True Lark's internal team was unable to dedicate the necessary time to data annotation without neglecting other critical aspects of product development. This led them to seek external assistance from CloudFactory for data labeling operations.

About Customer

True Lark is an AI communications platform that offers a virtual business assistant named Sasha, designed to handle customer inquiries, book appointments, and make purchases around the clock. The company primarily serves personal service businesses such as dental offices, spas, and exercise studios, which require efficient customer engagement and lead management. Founded by Srivatsan Laxman, True Lark leverages AI to address the unmet potential in the personal service sector, providing automated conversational experiences that enhance customer service and operational efficiency. CloudFactory supports True Lark by annotating large volumes of customer conversations, enabling the company to focus on AI model innovation and rapid productization.

Solution

True Lark partnered with CloudFactory to handle the data annotation tasks required for training their AI models. CloudFactory's team was trained to understand the nuances of language necessary for accurate text tagging. True Lark initially spent time explaining the requirements to CloudFactory, which then took over the process of reviewing and labeling large batches of text message conversations. The annotations included identifying nouns, appointment times, staff members, and service types, as well as determining the nature of client requests. This collaboration allowed True Lark to focus on testing and training their AI models, leading to significant improvements in their virtual assistant, Sasha.

Impact #1	True Lark's AI team regained 90% of their workday, allowing them to focus on innovation and product development.
Impact #2	The partnership with CloudFactory provided a long-term solution for data annotation, ensuring continuous improvement of the AI models.
Impact #3	True Lark successfully tested and trained their models, receiving positive feedback from CloudFactory on the improvements made.

Impact #1

True Lark's AI team regained 90% of their workday, allowing them to focus on innovation and product development.

Impact #2

The partnership with CloudFactory provided a long-term solution for data annotation, ensuring continuous improvement of the AI models.

Impact #3

True Lark successfully tested and trained their models, receiving positive feedback from CloudFactory on the improvements made.

Benefit #1	90% of the workday was freed up for True Lark's internal team.

Benefit #1

90% of the workday was freed up for True Lark's internal team.

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Overview

Building a better chatbot with text annotation services

Operational Impact

Quantitative Benefit