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.
$500
per month per subscription
SAP Conversational AI (discontinued)
Score 6.8 out of 10
N/A
SAP Conversational AI was a platform used to build chatbots and digital assistants in SAP integration. Starting January 2023, SAP Conversational AI, SAP’s chatbot building platform has been set to maintenance mode. Existing customers can continue to use the enterprise edition of the product until the end of their contract.
N/A
Pricing
IBM watsonx Orchestrate
SAP Conversational AI (discontinued)
Editions & Modules
Essential
$500
per month per subscription
Essentials
$500
per month Per subscription
Standard
Enterprise
Standard
Enterprise
per month Per subscription
No answers on this topic
Offerings
Pricing Offerings
IBM watsonx Orchestrate
SAP Conversational AI (discontinued)
Free Trial
Yes
Yes
Free/Freemium Version
No
Yes
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
Optional
No setup fee
Additional Details
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.
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More Pricing Information
Community Pulse
IBM watsonx Orchestrate
SAP Conversational AI (discontinued)
Considered Both Products
IBM watsonx Orchestrate
Verified User
Anonymous
Chose IBM watsonx Orchestrate
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 …
The other solution provides far more capabilities but at a much higher price and far more complexity. The IBM watsonx Orchestrate tool is less expensive (about 25% of the other solution) while being good enough for what we needed and being easy to use.
Strong ITSM and HR workflow automation with governance, ServiceNow excels in IT/HR but lacks flexibility for cross-departmental use cases such as demand planning, finance close, or procurement analytics. Orchestrate supports a broader set of enterprise functions beyond IT …
Google Cloud Dialogflow, Amazon Lex, and Azure AI Bot Service were assessed before selecting IBM watsonx Assistant. The primary reason we used IBM watsonx Assistant is the ability to remember diverse contexts during the multiphase bookings and to support multiple languages that …
The code generation feature of IBM watsonx Assistant was slightly better than in ChatGPT and Vertex AI. However that might change in the future since AI engines are evolving very quickly.
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 …
My experience working with Microsoft Bot Framework and Dialogflow has shown that Watson Assistant features an intuitive interface combined with powerful analytics. We selected Watson Assistant because it strikes an excellent balance between providing powerful capabilities while …
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 …
I selected IBM watsonx Assistant so I could maintain the NLP/NLU processing from our last supplier (which was not Twilio). Since we switched, I have not liked IBM watsonx Assistant so much. We are sincerely thinking about changing it to a new one, the Kore.AI which seems easier …
They are ideal for creating different chatbots for different business entities. It supports different languages, I can implement it with messaging platforms like Slack, Telegram, and many more...
SAP Conversational AI has been a great help in analyzing common errors in data processing and analytics. It is important to understand scenarios that apply in this situation as information is constantly being gathered, which is where SAP Conversational AI is able to help …
The platforms have similarities in terms of making the organization more data-driven. However, the use cases are different. SAP analytics cloud is used for reporting, deploying dashboards, and scheduling timely delivery of reporting and analytics. SAP Conversational AI is a …
Since Alexa and Teams have their own UI for bots they rank better when it comes to usability and features provided. Voice enablement seems to be a big drag.
We decided to go ahead with this product since our systems heavily rely on SAP already. The integration of data is seamless and can be customized to all needs. We found other competitive solutions to be worse at the data integration, although sometimes they provide a nicer UI …
SAP Conversational AI is on par with Oracle Digital Assistant in most respects assuming you are using SAP Conversational AI with SAP HANA and Oracle Digital Assistant with Oracle Cloud + Oracle Database. SendBird is much better in chat user experience and scaling with number of …
SAP Conversational AI is superior to rule-based solutions because they cannot understand a plurality of words such as synonyms. Rule-based systems may for example search for trigger words like "invoice" or "receipt" and recognize those just as well as the neural (?) models used …
SAP Conversational AI has a better documentation of their APIs. SAP Conversational AI also has a much more active and friendly community with lots of help from the community as well as from SAP co-workers. The integration with SAP (as non-SAP) technologies surpasses that of the …
Google Dialogflow has the same global experience, but SAP CAI is better for non-developers. There is a way better experience in SAP CAI than Ideta, and SAP was also cheaper and easier to deploy.
The Mirosoft bot framework is less user focused and more aimed at developers. I would recommend using SAP Conversational AI in scenarios, where people in the marketing division have to use the bot and implement new questions. For small to medium sized conversations I would …
Conversational AI is a lot leaner than the competition, especially compare to Botpress and Microsoft whose frameworks feel less convincing to managers. SAP also provides key use cases with both their own technologies and third-party solutions and the underlying chatbot platform …
Our scenario was pretty clear. We looked for an enterprise chatbot platform that could support SAP ERP like S/4HANA. Recent features make going with SAP CAI the clear choice for someone who wants to build bots around S/4HANA.
We selected SAP Conversational AI because we are a big group in constant development that invests in technology that is easy to use and has a good support community.
The easy implementation of SAP Conversational AI makes it stand out against any other tool. In turn, the free implementation for a PoC opens the game to give demos to promote its use to potential customers. Recently they launched the web client to implement a bot in SAP Cloud …
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.
It would be most suitable to help you attain swift conversation flows as you engage with your audiences. The bots are also of indispensable value in handling repetitive tasks around the firm such as automated HR resourcing expeditions or marketing campaigns or any other important but monotonous tasks. I however admit that analyzing the bot's performance is quite complex, have an RPA specialist around.
SAP Conversational AI in addition to providing the chatbot features also integrates bot analytics without the need for much setup/deployment work.
It is possible to code SAP Conversational AI chatbot in multiple coding languages (Node.js, Python, PHP, iOS, etc.) that makes it easy both implement as well as integrate with existing IT stacks (eg. Analytics, AI, Databases).
SAP Conversational AI is easy to implement and get it running especially if you are already using SAP S/4HANA Cloud.
Documentation update. Some of the very nice tutorials and docs seem outdated or not SAP-branded, which can be confusing
Fallback channels. The intercom fallback channel has an important lack of speed, and the SAP fallback channel seems complicated to implement in a product development sprint
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.
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.
Chatbots have already acquired most of the market and are still trending with the needs of changing market everyday. It will keep evolving with AI and NLP more to offer for improvements. SAP CAI is a good product to add to an enterprise using SAP ERP Suite
Never had an issue. SAP CAI shares the same platform as any other product hosted on SAP Cloud Platform (aka BTP) and depends on your hosting (US, Europe, Asia). Maintenance modes are planned and customers are aware of it well in advance in order to mitigate potential impacts on the service offering.
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.
It's a pure SaaS platform hosted on SAP Cloud Platform (aka BTP). The experience is pretty much seamless with minimum loadings or noticeable lags. The hosting depends on your location so you may want to make sure the instance is available on a server close to you, such as the USA, Europe or Asia.
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!).
Great support from the people of SAP Conversational AI as of the community. Sometimes it takes a little while for folks of the SAP Conversational AI team to answer but this has mostly to do with the overload of questions and users the product has. The gold-support channel within Slack that SAP Conversational AI has, is a great help to distinguish more professional usage and therefore more urgent questions.
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.
SAP Conversational AI has been a great help in analyzing common errors in data processing and analytics. It is important to understand scenarios that apply in this situation as information is constantly being gathered, which is where SAP Conversational AI is able to help provide common issues to be resolved. Data-driven and AI responding is the future of software analysis.
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.
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.
The impact has been very positive for our business objectives. Through the chatbot, our clients can have an immediate response to any of their requests without the need of an intervention of a person or without the use of the telephone or email. Customer satisfaction has been much higher.