With the rise of large language models (LLMs) such as ChatGPT and GPT-4, many are wondering if it is possible to create their own artificial intelligence (AI) chatbot using data from their company databases. Is this even feasible, and can language models offer such capabilities?
In this article, we reveal what is needed to create a ‘private ChatGPT’ that utilizes the data we provide. We will explore the advantages of this technology, as well as how we can overcome its current limitations.
Using Templates
To create a chatbot, we need a conversation database to train the AI model, and since the entire process is quite time-consuming, solutions already exist online. For example, Tidio is a platform that offers free tools for building chatbots that recognize user intents. It also allows us to train the chatbot by uploading conversations, notes, or text messages.
If you do not want to use a no-code chatbot development platform, there are numerous other options available. If you are into programming and interested in machine learning, you probably already know that you should consider Dialogflow API (owned by Google) as your primary tool.
Creating a basic chatbot is extremely simple and accessible to everyone. There are countless online bot development tools that we can use for free. However, creating a chatbot for a website is slightly easier for beginners than creating bots for social media. The best and probably easiest way to create your first chatbot is to use templates.
So, you simply select the bot that interests you and open it in the editor. This way, you will be able to see how it is designed and change the messages or conversation flow logic as desired. Platforms such as Tidio, Botsify, or Chatfuel allow us to play with chatbot templates or create from scratch.
