SAP Conversational AI (discontinued) vs. TensorFlow

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
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
TensorFlow
Score 8.0 out of 10
N/A
TensorFlow is an open-source machine learning software library for numerical computation using data flow graphs. It was originally developed by Google.N/A
Pricing
SAP Conversational AI (discontinued)TensorFlow
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
SAP Conversational AI (discontinued)TensorFlow
Free Trial
YesNo
Free/Freemium Version
YesNo
Premium Consulting/Integration Services
YesNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
SAP Conversational AI (discontinued)TensorFlow
Considered Both Products
SAP Conversational AI (discontinued)
Chose SAP Conversational AI (discontinued)
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 …
Chose SAP Conversational AI (discontinued)
Easy development on it and great integration with other platforms.
TensorFlow

No answer on this topic

Top Pros
Top Cons
Best Alternatives
SAP Conversational AI (discontinued)TensorFlow
Small Businesses
Front
Front
Score 8.8 out of 10
Jupyter Notebook
Jupyter Notebook
Score 9.2 out of 10
Medium-sized Companies
Genesys DX (discontinued)
Genesys DX (discontinued)
Score 10.0 out of 10
Posit
Posit
Score 9.8 out of 10
Enterprises
Genesys DX (discontinued)
Genesys DX (discontinued)
Score 10.0 out of 10
Posit
Posit
Score 9.8 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
SAP Conversational AI (discontinued)TensorFlow
Likelihood to Recommend
7.4
(37 ratings)
6.1
(15 ratings)
Usability
7.7
(2 ratings)
9.0
(1 ratings)
Availability
8.2
(2 ratings)
-
(0 ratings)
Performance
8.2
(2 ratings)
-
(0 ratings)
Support Rating
6.5
(32 ratings)
9.1
(2 ratings)
Implementation Rating
-
(0 ratings)
8.0
(1 ratings)
User Testimonials
SAP Conversational AI (discontinued)TensorFlow
Likelihood to Recommend
SAP
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.
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Open Source
TensorFlow is great for most deep learning purposes. This is especially true in two domains: 1. Computer vision: image classification, object detection and image generation via generative adversarial networks 2. Natural language processing: text classification and generation. The good community support often means that a lot of off-the-shelf models can be used to prove a concept or test an idea quickly. That, and Google's promotion of Colab means that ideas can be shared quite freely. Training, visualizing and debugging models is very easy in TensorFlow, compared to other platforms (especially the good old Caffe days). In terms of productionizing, it's a bit of a mixed bag. In our case, most of our feature building is performed via Apache Spark. This means having to convert Parquet (columnar optimized) files to a TensorFlow friendly format i.e., protobufs. The lack of good JVM bindings mean that our projects end up being a mix of Python and Scala. This makes it hard to reuse some of the tooling and support we wrote in Scala. This is where MXNet shines better (though its Scala API could do with more work).
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Pros
SAP
  • SAP has helped me manage my teams cost in material management.
  • SAP Conversational AI has provided with the goal of developing bot analytics to respond to common user face issues when reporting troubleshooting issues with software equipment as well as technical equipment.
  • Has helped deploy new bots to increase response time to employees who require assistance with ordering equipment software as well as application development in software ordering.
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Open Source
  • A vast library of functions for all kinds of tasks - Text, Images, Tabular, Video etc.
  • Amazing community helps developers obtain knowledge faster and get unblocked in this active development space.
  • Integration of high-level libraries like Keras and Estimators make it really simple for a beginner to get started with neural network based models.
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Cons
SAP
  • SAP can certainly provide better and more clear documentation on how to customize and deploy the chatbot/use SAP Conversational AI.
  • There is lot less developer community around SAP Conversational AI so it is hard to get help from outside developers and experts on best practices, hacks and existing applications/integrations.
  • It is hard to use SAP Conversational AI outside SAP S/4HANA Cloud, for example on AWS or GCP or in a multi cloud environment.
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Open Source
  • RNNs are still a bit lacking, compared to Theano.
  • Cannot handle sequence inputs
  • Theano is perhaps a bit faster and eats up less memory than TensorFlow on a given GPU, perhaps due to element-wise ops. Tensorflow wins for multi-GPU and “compilation” time.
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Usability
SAP
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
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Open Source
Support of multiple components and ease of development.
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Reliability and Availability
SAP
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.
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Open Source
No answers on this topic
Performance
SAP
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.
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Open Source
No answers on this topic
Support Rating
SAP
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.
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Open Source
Community support for TensorFlow is great. There's a huge community that truly loves the platform and there are many examples of development in TensorFlow. Often, when a new good technique is published, there will be a TensorFlow implementation not long after. This makes it quick to ally the latest techniques from academia straight to production-grade systems. Tooling around TensorFlow is also good. TensorBoard has been such a useful tool, I can't imagine how hard it would be to debug a deep neural network gone wrong without TensorBoard.
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Implementation Rating
SAP
No answers on this topic
Open Source
Use of cloud for better execution power is recommended.
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Alternatives Considered
SAP
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.
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Open Source
Keras is built on top of TensorFlow, but it is much simpler to use and more Python style friendly, so if you don't want to focus on too many details or control and not focus on some advanced features, Keras is one of the best options, but as far as if you want to dig into more, for sure TensorFlow is the right choice
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Return on Investment
SAP
  • 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.
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Open Source
  • Learning is s bit difficult takes lot of time.
  • Developing or implementing the whole neural network is time consuming with this, as you have to write everything.
  • Once you have learned this, it make your job very easy of getting the good result.
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ScreenShots

SAP Conversational AI (discontinued) Screenshots

Screenshot of Transform your customer and employee experience with SAP Conversational AI, which combines a powerful bot building platform and a digital assistant nicknamed CoPilot.Screenshot of Bot Training – Plug human-like understanding in your chatbots.Screenshot of Bot Builder – Build adaptable conversational flows through a powerful and visual tool.Screenshot of SAP Conversational AI provides a powerful building platform that allows the building of end-to-end chatbots as well as the customization of your digital assistant.Screenshot of Leverage the power of our highly performing NLP technology capable of building human-like AI chatbots in any language.Screenshot of Understand how your chatbot is used and leverage that data to improve the performance of your dataset.