About Rasa Stack

Rasa is the leading conversational AI platform, which allows individual developers across large enterprises to create superior AI assistants and chatbots. Rasa provides the tools and infrastructure necessary for building the very best tools that meaningfully transform how customers communicate and interact with businesses. With Rasa, all teams can create automated, personalized interactions with customers, at scale.


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4 Reviews of Rasa Stack

Overall rating

4.75 / 5 stars

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February 2021

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shushant from Infodevelopers Pvt Ltd

Verified Reviewer

Company Size: 201-500 employees

Industry: Computer Software

Time Used: More than 2 years

Review Source: Capterra


Ease-of-use

5.0

Value for money

4.0

Customer support

5.0

Functionality

5.0

February 2021

Why Rasa

I have been using Rasa stack for chatbot development for the past three years. I have developed multiple chatbot systems using Rasa.

Pros

Rasa is probably the best python framework for building NLP based chatbot system. The machine learning models that has been used for intent classification, entity recognition and NLG models are highly accurate. The data format is very easy to interpret from Rasa.

Cons

There are no any features that I do not like about Rasa.

Reasons for Choosing Rasa Stack

We can build custom chatbot systems and try out different ML models with Rasa stack

February 2021

Beebek from Gramin Institute

Verified Reviewer

Company Size: 11-50 employees

Industry: Computer Software

Time Used: More than 2 years

Review Source: Capterra


Ease-of-use

5.0

Value for money

5.0

Customer support

3.0

Functionality

4.0

February 2021

Rasa Review

Very good experience using rasa

Pros

Rasa is a great tool for building AI powered chatbots. It's intent classification models are very accurate and named entity recognition models are also highly accurate.

Cons

Integrating rasa chatbots with other comunication channels documentation should be improved

Reasons for Choosing Rasa Stack

We can tweak with different machine learning models with rasa

February 2021

Madhav from Global IME Bank

Verified Reviewer

Company Size: 201-500 employees

Industry: Banking

Time Used: More than 2 years

Review Source: Capterra


Ease-of-use

5.0

Value for money

5.0

Customer support

5.0

Functionality

5.0

February 2021

Why Rasa

Very good experience using Rasa Stack

Pros

I had used Rasa to develop a chatbot system for our bank and i found it the most suitable tool for building chatbot systems. The way Rasa takes in input data for the chatbot and the training time for such chatbots being really low is awesome.

Cons

I found debugging in Rasa difficult die to action server and rasa server running separetely on different servers.

February 2021

Anonymous

Verified Reviewer

Company Size: 1,001-5,000 employees

Time Used: Less than 6 months

Review Source: Capterra


Ease-of-use

5.0

Functionality

5.0

February 2021

One of the best frameworks for building chatbots and virtual assistants

I recently used Rasa to build a chatbot integrated with a FAQ.

Pros

I believe it is an excellent python framework. It is very simple to build both the NLU model and to configure the pipeline to use extremely powerful models of preprocessing and classification of intentions and entities. I also found it very intuitive to declare everything in the domain and work with stories and rules. Other structures such as slots and forms are also very practical and make all the difference when building the bot.

Cons

I liked all the features I found in RASA and they all helped in the development. I also thought the integration with some channels was easy.