IBM watsonx Assistant

The only reason is that we have been using some other products of IBM, and the trust on their company, so we chose to use IBM Watsonx Assistant, that's it.

Watson proved to be better and easier to use than Dialogflow. As for Twilio, we used it as an orchestrator in conjunction with Watson.

Tidio is very very basic and it is not having adequate NLP understanding let alone be sarcasm in language that is a far far distant thing so that's why it was a no from my end to Tidio.With Chatfuel there was only English language in focus and for our business we needed the both of above mentioned limitations so that's how I landed to watsonx Assistant and it worked quite fine for me leveraging everything I was missing out on.

I mean Einstein is fine and is going into the right direction but it's a bit limited for now. In the future it will be fine. IBM watsonx Assistant is more reliable, more intuitive, more natural and pretty much has what you need. Using Einstein is great in some particular and basic scenarios, however IBM watsonx Assistant is something you would implement pretty much everywhere.

IBM watsonx Assistant more simple and IBM support team very Professional

Watsonx Assistant is distinguished by its ability to understand natural language and its ability to adapt and learn over time. This allows for a more natural and personalized interaction with customers, enhancing the user experience. In addition, Watson Assistant offers a wide range of advanced features, such as intent recommendations, disambiguation, speech and text integration, and conflict resolution.

Those tools are complimenting each other, in my short interaction with this tool, this is like having a gen-AI tool that work for your business with a comprehensive documentation and available technical support to answer your questions. Bear in mind that this solution can be up and running in matter of hours, so measure your load and ROI carefully, as once you go using this kind of tool, it will be hard to have a same consistency level if you are using human agent

IBM watsonx is clearly superior to yellow.ai. Compared to Google Dialogflow is a tight comparison.

They are related - coming from the stable of IBM only. IBM Watson assistant specifically suited my pilot project because it was pretty straightforward and intuitive. IBM Watson Studio seemed to me like more of a super set, which could easily have all the features of IBM Watson Assistant - but then, the price also would be higher.

IBM Watson Assistant has a competitive cost structure, is easy to integrate with Intercom, and is more scalable as we look to future enhancements such as speech-to-text, document upload/analytics, and natural language processing across multiple languages.

IBM technical support / case resolution is good.

IBM updates / communication, product enhancements are clearly communicated.

Its a great tool to use it in conversational chatbots, data retrieval virtual agent very easily. It provides results with good accuracy. Development is not a big task, its almost ready enterprise product.

Mainly the UI of DialogFlow is not at all developer friendly which will definitely move you to IBM Watson [Assistant] which has the clear UI with multiple options arranged in [a] usable manner.

IBM Watson Assistant is doing great as other tools directly search from the internet and it need to understand all the algorithm to fetch the right answer. Also design of this is very difficult as they need to much of data feed where as IBM's tool can train by itself using both adaptive and predictive studio.

Its in Great shape and looking forward for more enhancements.

IBM Watson Assistant provides a highly intuitive and user-friendly interface, making it accessible to non-technical users to easily create and deploy conversational agents. Additionally, being a cloud-based platform, it eliminates the need for manual retraining of the bot after each modification, saving time and resources for businesses. This combination of user-friendliness and automation makes watsonx Assistant an ideal choice for building conversational agents at scale.

Currently we are using IBM cloud and IBM Watson in our project

I always used IBM Watson Assistant.

I have not yet evaluated other products like IBM Watson Assistant, but I have read that Kore.ai competes well with IBM Watson Assistant for the first place as a market leader, and it has won the first place due to a number of reasons, including a more intuitive and customizable UI, a huge library of APIs and more extension possibilities, especially with open source tools. Not to mention that IBM Watson Assistant is slightly more expensive than Kore.ai in terms of subscriptions. I look forward to evaluating Kore.ai with a hands-on approach in order to be able to provide a more thorough review of the product in the near future.

WA unifies several features of the products presented above, in a way that simplifies the creation of a bot that uses conversational features. Compared to competing products, WA presented more features compatible with my needs, which include variable responses depending on the intent and entities identified during data collection with the user.

Microsoft NLP approaches are interesting and powerful, but they don't have an easy way to model the interaction between actions like Watson, and they don't have a powerful way to test your virtual agent while you build them. Salesforce Einstein is a basic platform and doesn't have a powerful NLP engine.

It provides more interactive options for users to engage

Microsoft's NLP approaches are interesting and powerful, but they don't have an easy way to model the interaction between actions like watsonx, and they don't have a powerful way to test your virtual agents while you build them. Salesforce Einstein is a basic platform and doesn't have a powerful NLP engine.

IBM Watson Assistant is way more generic than ManyChat. It delivers more functionality and gives developers that flexibility to do whatever they want, pretty much. It is also way better in terms of natural language understanding and understanding concepts such as time, money, and people's names. IBM Watson Assistant also offers APIs that makes it very easy to programmatically generate and manipulate conversations in realtime.

My company is currently using Adobe Analytics, as we use a variety of products from the Adobe suite, so it has integrated very well. In comparison, the learning curve was little to non-existent as our experience with trials and training, let alone customer support from Adobe was 7-star worthy. Salesforce Einstein does not compare to the level of feedback and product capabilities that Watson or even Adobe offer, but it's a great starting point for smaller companies that lack the budget or analytics team for the actual analytics from these platforms. SAP was a bit of a thunderstorm experience - we had power and system outages while implementing, so we never got the full experience. Yet our IT department said there was something strange about the integration that caused us to have to overhaul our entire intranet after we exited that product's usage.