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Improving Customer Support: LangChain based Helpdesk & LLM-Powered AI Chatbot

Updated 15 January 2024

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In today’s digital age, customer support is more important than ever before. Customers expect to get help quickly and easily, no matter where they are or what time it is.

Today there are a number of ways that businesses can improve their customer support using machine learning and artificial intelligence.

One way is to utilise LangChain, which is a framework for developing applications powered by Large Language Models and Generative AI.

Helpdesk System Powered by AI

We can use the LangChain framework with any helpdesk system such as UVdesk and integrate with popular LLMs such as GPT-3. It will allow us to use NLP (natural language processing) and automate the process of finding, managing, and providing relevant knowledge bases and FAQ articles to customers.

Moreover, the LangChain helpdesk solution can automatically perform actions such as handling support tickets to escalate, reassign, or replying to clients on its own.

Helpdesk System Powered By AI

LangChain-powered helpdesk solution can free up human support agents to focus on more complex issues, and it can also make it easier for customers to find the information they need.

Another way to improve customer support is to use an LLM-powered AI chatbot for example, using ChatGPT for customer support. An LLM-powered AI chatbot is a chatbot that uses a large language model to generate responses to customer queries.

This can be a great way to answer simple questions and provide basic support. It can alsocollect customer feedback and identify potential problems.

Before proceeding further, let us learn what exactly is LangChain and how it will work with a helpdesk software solution.

What is LangChain?

LangChain is a software development framework that makes it easier to create applications using large language models (LLMs). It provides a standard interface for interacting with LLMs, as well as a variety of tools and libraries for building complex applications.

LangChain is written in Python and JavaScript and is available under the MIT license. It is currently under development, but it has already been used to create a variety of applications, including chatbots, question-answering systems, and summarization tools.

How LangChain based Helpdesk Work?

A LangChain-based helpdesk can learn and feed using your own custom datasets such as your organisation’s resources, company websites, user guides, or other relevant sources that are specifically meant for your customers.

You can feed your LangChain helpdesk with your data using various file formats such as csv, docx, epub, json, pdf, text, or unstructured databases.

So instead of training from a large corpus of random and irrelevant data, a LangChain-based helpdesk solution can be conditioned and fine-tuned to provide more high-quality and accurate results to your clients.

This means that businesses can create and provide knowledge bases answers to customers that are automatically updated with new information, and they can also create new knowledgebase content that is tailored to specific customer segments.

How LangChain Based Helpdesk Work

When a customer submits a question, the LangChain helpdesk will first try to find an answer in its stored database known as Vector Storage. If an answer is not available, the helpdesk will then generate a response based on the customer’s question.

The response can be a link to a relevant article in the knowledge base, it can be a summary of the information in the knowledge base, or it can be a custom response from the helpdesk resources.

How LLM-powered AI Chatbots Work?

An LLM-powered AI chatbot uses a large language model to generate responses to customer queries. This means that chatbots can understand complex questions and generate human-like responses.

LLM-powered AI chatbots can answer a wide range of customer questions. They can:

  • Answer simple questions about products or services
  • Provide support for complex issues
  • Collect customer feedback
  • Search information from backend

When LangChain familiarises and fine-tunes with your custom data, the AI chatbot will adapt itself to become relevant to your business domain.

For example, LangChain with E-commerce data can allow chatbots to connect with the online store backend, search database and provide more personalized replies to shoppers.

Benefits of Using LangChain Helpdesk and LLM Powered AI Chatbots

There are a number of benefits to using a LangChain-based helpdesk and an LLM-powered AI chatbot. These benefits include:

 Benefits Of Using LangChain Helpdesk And LLM Powered AI Chatbots

  • Improved customer satisfaction: Customers are more likely to be happy with their experience if they can get help quickly and easily.
  • Reduced costs: By automating customer support tasks, businesses can reduce the costs associated with customer support.
  • Increased efficiency: By using a LangChain-based helpdesk and an LLM-powered AI chatbot, businesses can free up customer support agents to focus on more complex issues.
  • Improved customer engagement: By providing customers with a variety of ways to get help, businesses can improve customer engagement.
  • More relevant results: Businesses can train their models on their own custom datasets to provide more accurate information to their customers.

Further, read more on how large language models in ecommerce can play a very important role and be really useful for businesses.

Conclusion

A LangChain-based helpdesk and an LLM-powered AI chatbot can be a great way to improve customer support. But what we need is to train these AI models with the right data, so that they can provide results that are narrower and specific to the query asked.

So by using these technologies such as LangChain, LLMs, and Generative AI, businesses can make it easier for customers to get help, reduce costs, and improve customer satisfaction. Also, explore Webkul’s Large Language Model development services.

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