AWS provides Amazon Lex, a chatbot building technology.
$0
Per Speech Request
Rasa
Score 6.0 out of 10
Enterprise companies (1,001+ employees)
Rasa is a conversational AI platform from the company of the same name headquartered in San Francisco, enabling enterprises to build customer experiences. Rasa’s platform was built to create enterprise-grade virtual assistants, allowing personalized conversations with customers - at scale. Rasa’s conversational AI platform allows companies to build better customer experiences by lowering costs through automation, improving customer satisfaction, and providing a scalable way to gather customer…
If you wish to quickly deploy multilingual chatbots without having to worry about infrastructure and model training, go for Amazon Lex. It is one of the best general-purpose conversational AI solutions in the market. The cherry on the cake is that it also seamlessly integrates with other AWS services, so you would be good there. Performance monitoring is very easy with AWS. It has support for both text and integration. If you are not a pro-NLP expert, Amazon Lex will make your job really easy.
Rasa Pro is well suited for corporate use and for chatbots which require backend connections. Smaller chatbots with a few flows might be better served with a simple dialogue engine and custom AI agents, or Rasa Open Source. Rasa does not come with its own complex vector database, just in-memory FAISS and connectors to external vector DB's such as Milvus and Qdrant. It provides only a basic document parser and embedder for FAISS. If you need to build a RAG focused chatbot around a large knowledge base with complex documents, e.g. lots of MS Word or PDF files, you'll have to build a separate document parser and embedder, as well as your own semantic search engine
Easy to deploy and very easy to integrate with other AWS services. Automating simple tasks is also very easy with Amazon Lex. We never had NLP experts in our team, but we were still able to deploy chatbots for our support functions with minimal issues. Native integration with other AWS services like S3 and Lambda has been of paramount importance.
With the help of dedicated team - documentation and video resources it is relatively easier to build. We prioritized pro-code usage to begin with launch.
Community support for Amazon Lex is good. Also, since it is an AWS service, the support has a similar standard as other AWS services. We have had a couple of instances of our bots weren't able to interact with our web apps. We reached out to the support team, and they were able to resolve our issue in no time. The documentation from the Amazon Lex team also makes creating chatbots a breeze.
Rasa support has been very responsive, trying to fix any reported issues ASAP. They've also listened to many requests for improvement. The Rasa features and changelog are well documented
