Table of Contents
Table of Contents
8+ Best Chatbot Development Frameworks for Any Budget & Occasion
Chatbot development frameworks have been around for a while. Many successful businesses use them to develop some form of a chatbot to engage with their customers.
But do you really need to have your own chatbot developed?
The answer is a strong yes. Why? Chatbots are one of the most engaging marketing automation tools, and they can contribute tremendously to your overall marketing strategy. For instance, 67% of global customers have interacted with a chatbot at least once in the past year.
Okay, chatbots might be helpful, but they are also complex and expensive to develop, right? Wrong. In 2021, chatbot development services became more accessible than ever. The turnaround times for chatbot development improved, and many more developers entered the market.
But the real challenge in chatbot development is to pick the proper chatbot framework for your business and hiring a chatbot expert that can deliver.
To make things easier for you, we hand-picked the seven best chatbot development frameworks for any business occasion. Ready to pick the best chatbot framework for your company? Read on!
Chatbots 101: Understand the Basics Before you Make your Pick
Before you pick the best framework for your business, let’s make sure you understand the basics of chatbot development:
A chatbot is an automated customer interaction system that analyzes user input and provides a detailed response to that input based on the information available in the chatbot database.
Chatbots provide a variety of benefits for your business:
- 24/7 customer support availability
- Immediate response time
- High response rates (35-40%)
- Reduced customer support costs
- Huge time-saver
- Automated storage of customer data
- Integrated with the CRM of your choice
There are two general types of chatbots:
- Simple, a.k.a. knowledge-based chatbots: These chatbots analyze customer queries based on the keywords entered, and then provide automated responses to such questions based on the information previously uploaded in the chatbot database.
- AI-powered chatbots: These chatbots use machine learning (ML) and natural language processing (NLP) technologies to generate the best responses for customer queries automatically. Such chatbots learn as they interact with more customers, and require some advanced training in the early stages.
Now that you understand all the basic chatbot terminology, let’s get to know our contestants.
8+ Best Chatbot Development Solutions: Picking Your Winner
You can create chatbot solutions using a variety of chatbot frameworks. To create a proper chatbot, you will have to hire a certified developer, who is familiar with the coding languages used to develop the chatbot framework.
Depending on the chosen framework, you can deploy your chatbots directly into your third-party apps, messaging platforms, or even electronic devices.
Now, let’s look at the best chatbot development frameworks and see what makes them unique.
#1: Dialogflow
| PROS | CONS |
|---|---|
| Supports both voice & chat | Lackluster support |
| Versatile API (Supports Alexa, Google Assistant, Slack, Twitter, etc.) | Steep learning curve |
| Easily Scalable | |
| 20+ languages supported |
Dialogflow is a Google-owned natural language learning platform used to develop a variety of chatbot solutions. It is a great fit for anyone looking for unmatched scalability, cross-platform capabilities, and both voice or text support.
You can integrate the chatbots created in Dialogflow into any significant social media network, and it would work seamlessly across all the platforms and devices thanks to Google’s powerful API.
#2: Microsoft Bot Framework
| PROS | CONS |
|---|---|
| Simpler to use | No native natural language processing support |
| Has 100+ pre-built chatbot templates | Limited to Node.js and C# |
| Visual flow builder | |
| Good support and tutorials |
Microsoft Bot Framework provides a user-friendly interface and comes preloaded with various bot templates to simplify the development process. It is a robust framework, making it a popular choice for developers knowledgeable in Node.js and C#.
On the downside, Microsoft Bot Framework does not have native NLP or voice recognition support. This makes it a bad fit for AI chatbot or voice assistant chatbot development. Moreover, it is not as easy to scale as the Google solution.
#3: Amazon Lex
| PROS | CONS |
|---|---|
| One-click cross-platform deployment | Limited chatbot hosting options |
| Unmatched conversational AI capabilities | Chatbot goes down if AWS goes down |
| Easy to scale | Occasional bugs |
| SDK for Ios, Android Devices | |
| Supports all messengers |
Lex is an Amazon-branded chatbot development framework that operates on AWS servers. It offers one of the simplest interfaces and is praised for the ease of use that it provides. Lex has unmatched conversational capabilities – it requires virtually no training time to process user input and provide automated responses.
Moreover, you can deploy Amazon Lex-enabled chatbots into any mobile application, messenger, or IoT devices, making it the best bank-for-the-buck chatbot that is beginner-friendly. Best of all, it comes with a powerful free version that has no development restrictions.
At last, Lex offers one of the best chatbot management consoles and allows you to deploy your chatbot cross-platform with just one click.
#4: Wit.ai
| PROS | CONS |
|---|---|
| Detailed API documentation + strong community support | NLP engine training takes a lot of time |
| Best for IoT | Hard to find missing parameters |
| Strongest NLP capabilities | |
| 130+ languages supported |
|
| Quick deployment on FB messenger |
Wit.ai was built to support Internet of Things (IoT) devices (smart homes, smartwatches, smart fridges, smart cars). This means that wit.ai would be a perfect choice for programmers dealing with chatbots in electronic devices.
While wit.ai is quite complex, the platform API documentation is detailed and beginner-friendly. It has one of the strongest natural language processing engines, which makes it a perfect choice for voice assistants, devices, cars, and messengers that have to deal with a lot of clients at once.
Best of all – it is a completely free framework.
#5: Botpress
| PROS | CONS |
|---|---|
| Highly-customizable | Steep learning curve |
| Native JavaScript support | It gets buggy as you add integrations |
| No-code environment for a bot manager | |
| Simple to learn |
Botpress is like WordPress but for bots:
- The platform is open-source and free
- You have countless developers creating plugins and integrations for it
- The community is thriving, and tons of information online
- Templates for bots.
Besides this, just as WordPress simplified web development, Botpress is also set to simplify chatbot creation.
While it might be one of the most rigorous chatbot frameworks, the documentation is highly detailed, and the communal support is strong, making it easy to get started.
#6: Rasa
| PROS | CONS |
|---|---|
| Personalized bot responses | Not suitable for beginners |
| Simple bot training | Knowledge of NLU/NLP required |
| Deploy on own servers (higher security of data) | Not all the info about possible bugs is available online. |
| Multiple development environments |
When it comes to natural language processing, bots usually analyze user input, and then look for the right answer in the pre-loaded database.
Rasa takes it a step further and allows you to create bots that behave like real humans in a conversation, creating their own responses.
Rasa natural language understanding (NLU) algorithms simplify the process of training your chatbot and enable your chatbots to look for information on their own, without much training. This makes Rasa the best fit for the development of support bots that require a deeper understanding of customer queries. Best of all – Rasa is a free platform.
#7: Pandorabots
| PROS | CONS |
|---|---|
| Integration with all major messaging platforms | Not suitable for IoT |
| Integrate your bots into third-party apps | Pricey |
| API access | AIML Language used for development works only with Pandora |
Pandorabots is the unicorn of all the chatbot development frameworks. It offers all the standard features of the high-quality chatbot development framework, but also takes an innovative development approach. Pandorabots uses a specifically-developed AI markup language (AIML) that allows creators to build AI-driven virtual agents that act like real humans. With extra 3D modeling added on top, the results look life-like, making pandora perfect for developing interactive chatbot models and business solutions.
#8: IBM Watson
| PROS | CONS |
|---|---|
| Most rigorous AI development platform | Tough to learn |
| Advanced ML engine | Lack of tutorials online |
| Customer data stored on a private cloud-only | Expensive |
| Automated interpretation of positive/negative responses |
IBM Watson is the most popular AI development framework used by some of the biggest companies in complex projects. It offers the highest standards of security and data storage.
Watson’s complex ML algorithms enable chatbots to interpret user queries and generate custom responses automatically. At last, bots developed on the IBM framework can be deployed into virtually any third-party application, messaging platform, or device.
Recap of Things to Keep in Mind When Creating Your Chatbots
As you can see, the world of chatbots is quite diverse. The final pick for your perfect chatbot development framework will depend on a few things. Here are a few questions that should help you make the right choice:
- Are you developing a customer service assistant, voice assistant, or a bot for a device?
- Which coding languages are your programmers proficient in?
- Do you need your chatbot to have AI capabilities?
- Should it be an open-source solution or a chatbot deployed on your own servers?
Answering these questions can help you narrow down the possibilities and make the right pick. If you are still unsure about the approach you take with chatbot development, we recommend you to contact Scopic for a free chatbot development consultation.
