How to choose the right chatbot

Based on your problems, you can either create a Conversational or a GPT-based chatbot. Let’s see their differences.

Conversational AI is a custom solution that can be fully integrated with your internal systems to further perform tasks like booking appointments. It may be useful but it lacks communication skills. This type of AI uses extensive datasets and continuous learning to adapt based on user interactions, making it highly customisable for specific needs and able to provide personalised responses. However, this means it can be more expensive and complex to implement.

GPT-based chatbots shine when it comes to communication. This type of chatbot mimics a conversation and can handle complex interactions while providing accurate information with ease. They are trained on large text datasets and are adept at generating text responses, but their real-time learning and adaptation are limited compared to Conversational AI. This makes them less customisable and their responses more generic, but particularly useful for businesses looking for a simple, cost-effective solution that can handle straightforward customer queries.

Key Differences

How can you create each bot?

Conversational AI:

1. Data Collection and Preparation: Gather a large dataset of text and code. This could include customer service transcripts, product descriptions, or any relevant information.
2. Model Training: Train the AI model on the dataset using machine learning techniques. This involves feeding the data into the model and allowing it to learn patterns and relationships within the data. Rasa is a great framework to speed things up!
3. Fine-tuning and Optimization: Fine-tune the model for specific tasks and optimise it for performance and accuracy. This might involve adjusting the model's parameters or adding more training data.
4. Integration and Deployment: Integrate the model into your existing systems and deploy it to your desired platform. This could involve creating a chatbot interface or integrating the model into your website or app.

GPT-based Chatbots:

1. Utilise Existing Platforms: Leverage existing platforms and frameworks designed for building GPT-based chatbots like OpenAI’s API. These platforms provide pre-trained models and tools to simplify the development process.
2. Collect your Data: If you want a more personalised experience you need to gather all your relevant data. This could be text-based data tables or even various documents that you want your chatbot to read. Remember, if you want specific results, a conversational chatbot might be the one for you.
3. Customise and Fine-tune: Customise the pre-trained models to your specific needs and fine-tune them on your own data. This allows you to tailor the chatbot's responses and behaviour to align with your brand and customer interactions.
4. Integrate and Deploy: Integrate the chatbot into your desired channels, such as your website, messaging apps, or social media platforms. Deploy the chatbot and monitor its performance to make any necessary adjustments.

Use Cases:

Conversational AI Chatbots:

1. Internal Task Automation: Automate routine tasks like employee onboarding, internal ticketing, or scheduling shifts, making it easier to manage operations.
2. Appointment Scheduling: Booking an Appointment or providing Information.
3. E-commerce Recommendations: Product suggestions based on customers needs

GPT Chatbots:

1. Advanced Customer Support: 24/7 complex query handling.
2. Content Generation and Marketing: Articles, social media posts.
3. Document Analysis: Speed-Up your reading through summary

To Sum it Up:

At the end of the day, you build what your problems demand.

Conversational AI might be the way to go if you need a highly customisable chatbot that can integrate with your existing systems and provide personalised responses.

However, if you're looking for a simple, cost-effective solution that can handle basic customer interactions, a GPT-based chatbot could be a better fit.