IBM watsonx Orchestrate vs. Rasa

In our case, it is well-suited for workday integration, which allows us to automate the entire workflow. However, we are still working on the O9 platform integration, which we feel is less appropriate, and integrating the workflow into the platform.

I have been using the platform for over 3 years and I have noticed a very good evolution, in an attempt to reinvent themselves. The support team is amazing, always available to work out with us in achieving the best results. About the technology, the algorithms available in the platform suits most of the cases. Being language agnostic is a very positive point for us, because some big tech platforms have little support for PT-PT language.

Incentivized

• Provides fast and accurate responses to our customers.
• Learns and adapts, continually improving its responses and recommendations as it interacts with customers.
• Integrates seamlessly with our internal systems and databases.
• We can customize and adjust the virtual assistant's responses and recommendations to suit our customers' specific needs.
• It provides valuable information about our customers' needs and preferences.

Incentivized

• Rasa team has Top notch AI knowledge
• Greate customer support, by listening towards the clients needs.
• And building future proof solutions around client Business Requirements within dazzling timeframes

Incentivized

• User experience in custom skills could be simplified.
• APIs are great... but form/website-based form interaction could be improved (as other similar products have.
• Training and documentation are delivered for 101 getting started, and when you need deeper technical understanding, documentation could be improved.

Incentivized

• Rasa CALM flows and Rasa domain could be made fully independent of the Rasa training process and dynamically retrievable from e.g. a graph DB. This would make the chatbot more flexible.
• Prompt templates, or at least paths could be referenced in Rasa config. Different policies in the Rasa config could then be configured without code change to use different prompt templates
• LLM configuration should rather be part of the endpoints, than model configuration.
• Rasa Studio could support all the functionality of Rasa Pro.

Incentivized

IBM Watson simply works well for my organisation. We were able to design, build, and deploy a fully integrated chatbot in a matter of months. The basic building blocks (intents, skills, dialogue nodes, integration) are relatively straightforward for a technical developer to work with. The bot now supports retail customers in 3 different countries on both web and app based channels. We plan to further develop the bot to expand the way it interacts with customers through voice to text, and optical character recognition, as well as an improved UI.

Incentivized

With the growing use of AI and chatbots, it's very easy to use, and the conversational language makes it easier than keyword searches in a document. The contextual language processing is impressive. It's easy to integrate into our internal portal. The use of this tool would depend on each company's security and data sensitivity.

Incentivized

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.

Incentivized

To develop chatbots based on client provided flow what kind chatbot required for client either button or free text chatbots. we will decided accordingly flow and develop chatbot using IBM Watson. We will integrated custom components if required which is not present in library. IBM Watson library anyone can easily learn and develop chatbots.

Incentivized

We've rarely had to engage support, but they've always been prompt in responding and very attentive. Support experiences have been extremely positive (but we're mostly happy that we just don't have any cause to routinely need support in the first place!).

Incentivized

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

Incentivized

Excellent course material.

Incentivized

Overall the implementation was simple.

Incentivized

I think this product's got a lot more use cases from a business standpoint. I find the other products are very based in end users and also the orchestrator has a lot more agnostic connections to a lot of products, whereas Microsoft is very Microsoft dominated and the other products are very technical and not business focused.

Incentivized

Glean - proprietary semantic search algorithms, no backend actions integration IBM Watsonx - complicated dialogue builder, poor separation of no-code and pro-code interfaces ELMOS (agent based) - all logic in code, no dialogue logic in no-code interface possible Rasa - transparent and simple sharing of objects between no-code and pro-code interfaces. Transparent LLM usage and restrictions. Simple backend integration via Rasa SDK

Incentivized

From past 3+ years I am using IBM Watson in our current project easily can implement and manage and monitor user how their using. Is there and update also just update dialog is just enough to change no need to touch any other templates. Multiple language will support, and action and dialog speak recognize chatbot we can create as per client requirement. Overall, as of now good experience with IBM Watson.

Incentivized

• The clients have received additional, rather enhanced, individual conversion rates of users who interact with the virtual assistant.
• Due to the introduction of automated methods of handling a majority of the calls that are made, many call center agents are thus left to handle only complicated cases.
• According to a more advanced understanding of patterns, the assistant has been critical in suggesting solutions and thus drove optional revenue management.

Incentivized

• Reduced Human Connected Calls Per active User
• Improved Calls disposed by Voice Agent
• Reduced call wait times

Incentivized