Tiledesk
Tiledesk is an open-source chatbot builder, but it comes to market with a disruptive idea. Imagine you can make a chatbot like a developer does but without needing to write code. That’s fantastic. You can design the conversation flow entirely with a visual interface, and there is no need for coding knowledge.
In the beginning, Tiledesk started with a Conversational AI space with low-code solutions, designing AI-powered conversations using markdown syntax.
That time we at Tiledesk discovered that small and medium size companies need help implementing automation conversation experience. Finally, we decided to do customer interviews with our “power users.” Based on their feedback, we are working on a new release of our AI-powered chatbot that will follow a completely new no-code approach.
Microsoft’s well-known open-source platform enables programmers to make their own bots quickly. It implements an active learning element that aids in enhancing user interaction. Since it is primarily code-driven, developers fully command over the chatbot-building process. It covers Skype, Email, Twitter, Telegram, and many more channels. It’s suitable for a business’ omnichannel strategy. The Microsoft bot framework would be a good option if you are a developer and need many bot templates or SDKs for multiple computer languages.
But there is a problem with Microsoft. The NLU (Natural language understanding) engine is not open-source; consequently, you cannot install it on-premise.
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Doubtless, OpenDialog would be among the best NLP (Natural language processing), allowing users to quickly design and prototype conversations. The USP of this framework is that it enables coding experience-free development of fully functional conversational bots by its machine-learning technology.
You can deploy, integrate, and teach chatbots effectively using OpenDialog. Users may adapt and combine this intelligent conversation engine as needed. You may employ the top AI methods for the given challenge thanks to the NLU technology (A technology that enables chatbots to have natural-language speech or text conversations with humans.)
GitHub source code
Rasa helps you to add human feelings to the interactions. This open-source framework has two major independent components. “Core and NLU” (Natural Language Understanding)
The NLU understands a user message, and Core decides what happens next. This framework can automate text-based and voice-based assistants and is compatible with communication channels like Facebook Messenger, Slack, Telegram, and Twilio, which provide customer data analytics.
Be aware that there are better options available for beginners. Before using RASA, you should be mindful of NLP, Python, Deep Learning, and other related technologies. And on the server side, creating a chatbot involves many resources.
GitHub source code
Botpress is a well-known open-source conversational Ai platform. It has a modular design, which allows you to develop chatbots in parts that can operate independently. Developers test Botpress from around the world to fix and limit bugs and errors. Specialists with different skills can build chatbots using visual conversation flows that Botpress designs.
You can give actionable chatbot analyses as you have complete control over the data that comes in and out. Then you can keep an eye on your results and make better business decisions.
GitHub source code
Wit.ai is an open-source chatbot builder that Facebook acquired in 2015. Since then, many businesses that use Facebook have used this framework too. Wit.ai is a well-documented platform that makes it easy for developers to get started. It is accessible in several languages, including Python and Ruby, and supports more than 100 languages with voice control features. It can integrate with websites, apps, and wearable devices to provide real-time responses, but as a downside, you need to know that the training process can be tough as there is much-unstated information.
GitHub source code
Another great option for free and open-source frameworks for building chatbots that supports NLP is Tock. Create intricate stories using the components offered by Kotlin, Python, or Node.js, or use Tock APIs to interact with any language. You can build up your platform to run in the cloud, on-premises, or even embedded, and Tock deploys in minutes utilizing Docker running settings.
GitHub source code
Amazon Lex is an open-source framework that integrates essential marketing software like HubSpot, Zendesk, and Salesforce. It supports different communication channels like Facebook Messenger, Twilio, and Slack. This open-source framework supports automatic voice recognition and has built-in machine learning and natural language processing (NLP engine)
There are two problems with this framework: first, difficulty in preparing data with the framework, and second, the only functional language with the framework is English.
GitHub source code
Thanks to this fantastic response framework, you may develop conversational apps with a better user experience than conventional chatbots. It was written using TypeScript and JavaScript and is distributed under the MIT License. This framework is appropriate for developers and helps them to create cutting-edge conversational apps that function with browser, mobile, and messaging platforms like Telegram and WhatsApp.
GitHub source code
Ana is a wonderful option if you’re seeking in-build services. But remember that to utilize this framework, you must be a developer. Button, text, and input field creation are made easier with the aid of Ana Studio. You can quickly include Ana in your program, thanks to SDK. And the simulator’s features, including memory display, let you manage your bot experience. For both personal and business usage, Ana is FREE. You can set up and begin producing ChatBots in about 30 minutes as a developer.
GitHub source code
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