Top 7 Frameworks for Building Chatbots: Comparison Table
This Table summarizes the key points of each framework along with factors to consider when making a choice:
| Framework | Open source/Proprietary | NLP Focus | Strengths | Limitations | Pricing |
|---|---|---|---|---|---|
| Dialogflow (by Google) | Proprietary | Strong | Beginner-friendly, Google Assistant integration, powerful NLP | Limited customization, Google-centric integrations | Free tier, Paid plans with increased features |
| Rasa (Open-source) | Open-source | Machine Learning | Highly customizable, machine learning for continuous improvement, open-source and cost-effective | Steeper learning curve, limited official support | Free |
| Microsoft Bot Framework | Proprietary | Varied | Enterprise-grade features, Azure integration, multi-language support | Less suitable for non-Azure projects, enterprise focus might be overkill for simpler chatbots | Free tier, Paid plans with increased features |
| Wit.ai (by Facebook) | Proprietary | Basic | User-friendly, simple integration, focus on core functionalities | Limited customization, future development roadmap unclear | Free tier, Paid plans with increased features |
| Botpress (Open-source) | Open-source | Basic | Visual development, open-source and customizable, multi-platform integration | Learning curve, limited functionality for complex chatbots | Free, Optional cloud hosting plans |
| IBM Watson Assistant | Proprietary | Advanced | AI powerhouse, enterprise-ready, extensive customization options | Steeper learning curve, tiered pricing structure | Free tier, Paid plans with increased features |
| Pandorabots | Proprietary | Basic | Rule-based control, highly customizable, established user base | Learning curve for rule-based development, less emphasis on AI | Free tier, Paid plans with increased features |
Top 7 Frameworks for Building Chatbots
At present, chatbots are everywhere, in both the real and virtual worlds. Customers contact them directly on business websites or messaging platforms and that’s how they deliver their services for both business and information seekers. This makes the customer-business relationship as well as the overall information-seeking process increasingly quick. Working on a chatbot from scratch is not easy, to say the least. This is where chatbot development frameworks come to help you out — they are loaded with tools and functions that make your process easier and make your conversational AI come to life.
This article exposes the ins and outs of chatbot frameworks, quoting the things you should consider when you are making a choice, and outlines seven outstanding ones. We will give an overview of each of those frameworks, covering their NLP capabilities as well as how efficiently they can be integrated into various platforms. At the end of this article, you will have enough knowledge to use the right framework in your own chatbot building.
Table of Content
- Why use Frameworks for Chatbots?
- Top 7 Chatbot Frameworks: Building Blocks for Conversational AI
- 1. Dialogflow (by Google)
- 2. Rasa (Open-source)
- 3. Microsoft Bot Framework
- 4. Wit.ai (by Facebook)
- 5. Botpress (Open-source)
- 6. IBM Watson Assistant
- 7. Pandorabots
- Top 7 Frameworks for Building Chatbots: Comparison Table
- Choosing the Right Framework