Although AI tools are functional on their own, if you want to integrate them into your business with maximum efficiency, you need to use AI agents. AI agents are tools that host various AI models and aim to automate complex workflows. There are AI agents on the market with multiple advantages and disadvantages, some require coding skills, while others have a UI as easy as drag and drop. One of the tools you can use when it comes to AI agents is LangChain. If you are wondering what LangChain is and what it offers, we’ve got you covered!

In this article, we will examine what LangChain is and explore its features.

Ready? Let’s dive in!

TL; DR

  • LangChain is a framework designed to make AI agent building easier.
  • With LangChain’s chains and links features, you can automate complex tasks by breaking them down into actionable steps.
  • LangChain’s main components include LLMs, prompt templates, AI agents, retrieval models, and knowledge bases.
  • LangChain offers its users features such as complex workflow automation, model communication, better LLM interface experience, and organization environment adaptation.
  • If you don’t want to deal with the building process and are looking for an AI agent that you can integrate directly into your organization’s workflow, TextCortex is the way to go.

What is LangChain?

LangChain is an open-source framework for building applications based on large language models (LLMs). You can automate your repetitive tasks with applications based on large language models. With LangChain, you can build AI agents that will automate complex tasks and lighten your workload by running different LLMs simultaneously. Moreover, with LangChain, you can build custom AI agents that meet the specific needs of your organization.

What is LangChain?

How Does LangChain Work?

Although it is possible to build AI agents that target specific tasks of your business with LangChain, you need to know coding languages ​​like Python. LangChain works with two different principles called chains and links. Chains cover a wide range of automated actions from user input to model output. With chains, you can connect different data sources, generate content, translate texts, and answer user questions. Another working principle of LangChain is links. Links allow you to divide complex chain tasks into multiple and smaller tasks. With LangChain’s links, you can complete tasks such as formatting user input and retrieving data from cloud storage.

How Does LangChain Work?

What are the Core Components of LangChain?

With LangChain, you can build AI agents that will automate specific tasks for your organization. LangChain provides its users with various components that give them customization options. Core components of LangChain include:

  • LLM Interface
  • Prompt Templates
  • Agents
  • Retrieval Modules
  • Memory

LangChain Pricing

LangChain is an AI agent framework that offers different pricing plans for both individual and organizational users. LangChain provides all features to enterprise and startup users and charges custom pricing. LangChain has two other pricing plans: developer and Plus. The LangChain developer pricing plan has all features except bulk data export and is free. The LangChain Plus plan charges $39 per month for each seat/user up to 10. It offers all developer features plus email support and security controls.

LangChain Pricing Plans

LangChain Features

LangChain aims to ease the workload of both businesses and organizations by offering various features. Let’s take a closer look at the features of LangChain.

Automation

With LangChain, you can automate most of your repetitive tasks by connecting links and chains. Using LangChain, you can automate tasks such as email writing, customer support, data analysis, and sending replies to customers. With LangChain, your AI agent can make and execute independent decisions in tasks you automate without the need for any human support. Moreover, thanks to the LLM support offered by LangChain, you can build AI agents that will cater to the needs of a wide range of departments, from the finance department to human resources.

Automation

Models Communication

The AI ​​agent models that you will build with LangChain are focused on generating perfect output by communicating with each other. When you assign an objective to an AI agent, the AI ​​models constantly communicate with each other and give feedback, and the leader AI model collects and combines all the outputs. The communication proficiency of an AI agent determines how high-quality and consistent output it will generate.

LangChain Models Communication

LangChain also makes it easier for users to communicate with models. Developers use prompts to communicate with AI models. LangChain provides a better user experience by correcting typos and minimal mistakes made by developers during communication with a library of frequently used prompts.

Data Integration

You can integrate custom databases into AI agents that you will build with LangChain and use its advanced data retrieval capabilities. LLMs such as GPT-4o and Claude 3.5 Sonnet are trained with fixed data and cannot use new data. However, you can train AI agents that you will build with LangChain with your data and use them in departmental tasks such as customer support. For example, you can analyze the databases that you will add to your AI agent and turn them into usable insights. At this stage, LangChain uses Retrieval Augmented Generation (RAG) technology to analyze and transmit its users' data correctly. This technology

Adaptation

AI agents that you will build with LangChain will gain the ability to make independent decisions by adapting to your organization’s workflow and environment. AI agents will analyze your organization’s working conditions, requirements, available resources, and data and choose the best method to achieve the given objectives. Thus, AI agents can adapt to your organization’s ever-changing environment and deliver better performance.

TextCortex

If you do not want to waste time building AI agents and are looking for an AI assistant that can directly adapt to the specific needs of your organization, then TextCortex is designed for you with its powerful RAG (Retrieval-augmented generation), multiple LLMs, AI image generators, 30,000+ integrations, knowledge bases, and web search feature. TextCortex aims to integrate into the workflow of enterprise users and automate complex tasks, saving time and workload for its users.

TextCortex also offers a conversational AI assistant, ZenoChat, which can provide individual support to employees of enterprises. ZenoChat is an AI chatbot that can integrate with your enterprise data, access up-to-date internet sources, and generate output with different tones of voice. With ZenoChat, you can complete a wide range of tasks, from email writing to data analysis, in seconds and increase the individual performance of your employees. Check out the results from one of our case studies:

  • TextCortex was implemented for Kemény Boehme Consultants as a solution to tackle these challenges and today employees report increased efficiency and productivity (saving 3 work days per month per employee on average).
  • AICX, an ecosystem partner of TextCortex, was integral to the onboarding and helped achieve a 70% activation rate of the team within the first weeks.
  • Employee confidence in using and working with AI increased by 60%.‍
  • The implementation results in a 28x return on investment (ROI).

Frequently Asked Questions

What exactly does LangChain do?

LangChain is a framework that allows users to build custom AI agents by communicating with AI interfaces. You need advanced Python knowledge to use LangChain. With LangChain, you can build AI agents that will meet the specific needs of your business or organization and automate complex tasks. If you need an AI that is already built and adapts to your enterprise, lightens your workload, and automates complex tasks, you can try TextCortex. TextCortex aims to integrate with its users’ workflows and automate their repetitive complex tasks.

How does LangChain differ from ChatGPT?

ChatGPT, developed by OpenAI, is an LLM that offers content generation to its users, while LangChain is a framework that allows its users to build AI agents that include a wide range of AI models, including ChatGPT. While ChatGPT requires user guidance and input to generate output, the AI ​​agents you build with LangChain can adapt to your organization’s environment and make and act independently.

Is LangChain safe to use?

Although LangChain did not contain any security violations originally, it is important to keep it constantly updated and take the necessary security measures. If you want to integrate an AI assistant that aims to protect your organization’s data and has SOC 2 Type I, SOC 2 Type II, and GDPR certifications into your workflow, TextCortex is the way to go.