Watsonx.ai is part of the IBM watsonx platform that brings together new generative AI capabilities, powered by foundation models, and traditional machine learning into a studio spanning the AI lifecycle. Watsonx.ai can be used to train, validate, tune, and deploy generative AI, foundation models, and machine learning capabilities, and build AI applications with less time and data.
$0
IBM watsonx Orchestrate
Score 8.4 out of 10
N/A
IBM® watsonx™ Orchestrate® leverages AI to automate complex workflows. The solution helps build, deploy, and manage AI assistants and agents. It offers a catalogue of pre-built agents and tools, low-code agent builder, multi-agent collaboration capabilities, and integrations with enterprise apps.
Pricing for watsonx.ai includes: model inference per 1000 tokens and ML tools and ML runtimes based on capacity unit hours.
IBM watsonx Orchestrate can be deployed and run on IBM Cloud, AWS, or on-premises. Prices shown are indicative, may vary by country, exclude any applicable taxes and duties, and are subject to product offering availability in a locale.
IBM watsonx.ai stands out in the ecosystem of artificial intelligence tools for its combination of flexibility, scalability and the ability to integrate multiple services in a single environment
IBM watsonx.ai se destaca no ecossistema de ferramentas de inteligência artificial …
It focus on enterprise level flexibility and it also provides us cloud and on prem both support which helps in integrating with legacy and modern systems. It has better compliance standards than other competitors. Better data governance and cost effective AI model which is very …
Similar positions for similar purposes include Google Cloud Dialogflow and Azure AI Bot Service that I have considered. As opposed to Dialogflow, IBM watsonx Assistant is more tightly linked to comprehensive analytical units that provide clearer and more comprehensive data …
Features
IBM watsonx.ai
IBM watsonx Orchestrate
AI Development
Comparison of AI Development features of Product A and Product B
I have built a code accelerator tool for one of the IBM product implementation. Although there was a heavy lifting at the start to train the model on specifics of the packaged solution library and ways of working; the efficacy of the model is astounding. Having said that, watsonx.ai is very well suited for customer service automation, healthcare data analytics, financial fraud detection, and sentiment analysis kind of projects. The Watsonx.ai look and feel is little confusing but I understand over a period of time , it will improve dramatically as well. I do feel that Watsonx.ai has certain limitations from cross-platform deployment flexibility. If an organization is deeply invested in a multi-cloud environment, Watson's integration on other cloud platforms may not be seamless comported to other AI platforms.
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.
New and improved natural language processing yielding better results helps the assistants understand the intention behind the query.
Preserves context of communication, allowing the customers to establish inquiries on the website and continue on the mobile app without having extra informational input.
Intelligent conversations mean that complex paths that are branched based on the user's inputs allow for a much more natural flow of the conversation than fixed scripts.
I think that it needs to be able to integrate better with the knowledge catalogs. It currently provides a default database, which isn't quite large enough for enterprise use. We can connect that then to an external source, but it'd be nice if we could able just to instantiate one straight away.
I still don't have enough experience, but i have seen a lot of demos and i have made some real world scenarios and so far so long every thing looks fine. I was at IBM Think 2025 and IBM TechXchange 2025 and the labs were really usefull and simple to understand.
Currently we are using 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. Action flow and dialog flow we are currently in chatbot.
I needed some time to understand the different parts of the web UI. It was slightly overwhelming in the beginning. However, after some time, it made sense, and I like the UI now. In terms of functionality, there are many useful features that make your life easy, like jumping to a section and giving me a deployment space to deploy my models easily.
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.
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.
I still don't have enough experience, but i have seen a lot of demos and i have made some real world scenarios and so far so long every thing looks fine. I was at IBM Think 2025 and IBM TechXchange 2025 and the labs were really usefull and simple to understand.
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!).
IBM watsonx.ai has been far superior to that of Chat GPT AI. the UI elements prompt responses and overall execution of the AI was much better and more accurate compared to the competition. I can not recommend using this platform enough. Great job IBM. I hope the team behind this project continues to grow and prosper.
Make has more community of workflows to follow that have been redeveloped and are available for download. Selecting WxO is based on our trust level with IBM and the propositions of the Granite model being less biased, more business trained, and the ecosystem allowing for expansion with Assistant and Discovery.
I still don't have enough experience, but i have seen a lot of demos and i have made some real world scenarios and so far so long every thing looks fine. I was at IBM Think 2025 and IBM TechXchange 2025 and the labs were really usefull and simple to understand.
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.
By automating tasks that would otherwise require human intervention, organizations may achieve cost savings in terms of labor, especially for handling large volumes of routine inquiries.
Virtual assistants can handle a large number of simultaneous interactions, making them scalable to accommodate growing customer bases and increasing workloads without a linear increase in staffing.