SAP Conversational AI (discontinued)

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 provide common issues to be resolved. Data-driven and AI responding is the future of software analysis.

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 more front-end product that end users can directly use to navigate the web application better. Both have strengths in their respective areas. Conversational AI is more recent and cutting edge.

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 architecture. The onboarding is also easier for SAP customers since it's integrated with the global SAP Identification framework, as well as the One Support Launchpad for incidents, etc.

I liked Alexa and Google dialog flow for the feature of Speech of bot and good response of a talking bot. however, building a bot easily without knowing much coding was possible in SAP CAI, which makes it a really good tool. The choice of product to go with also depends on the integrated systems in use and the business case. Hence, the call has to be made cautiously while choosing a platform for Bot.

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 consider Amazon Lex and IBM Watson Assistant but finally we choose SAP Conversational AI because we have many other SAP products in our company.

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 or additional functions.

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 users compared to SAP Conversational AI while Firebase is better in overall support and UI compared to SAP Conversational AI.

Not applicable.

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 by SAP Conversational AI, however, they cannot handle typos and do not deal well with other synonyms that the chat bot creator might not have conceived. We did not evaluate against other solutions in the industry, only against the hand-crafted programs.

Easy development on it and great integration with other platforms.

I've used Google Assistant which uses DialogFlow API. It seems to have excellent voice support out of the box compared to CAI.

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 competition. The better user interface is also a great advantage.

Intercom is featuring a similar product but without the same robust set of APIs.

We could have used the iOS native support for this kind of thing but it wouldn't have covered a scenario as difficult as ours.

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.

SAP Conversational AI’s natural language processor was much more efficient.

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 recommend Sap Conversational AI.

With built-in connection to SAP database (via SAP Cloud Foundry HANA studio), we believe it was a strong choice against AWS for the following:

• Information security/simplicity - All information remains under one SAP solution.
• Easy integration - No third party API needed to use or buy SAP CF. SAP CAI integrates easily.
• License - Pay per service is really good, we pay for only what we consume.

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.