IBM Watson Studio on Cloud Pak for Data vs. Lang.ai

It has a lot of features that are good for teams working on large-scale projects and continuously developing and reiterating their data project models. Really helpful when dealing with large data. It is a kind of one-stop solution for all data science tasks like visualization, cleaning, analyzing data, and developing models but small teams might find a lot of features unuseful.

Incentivized

I've been using Lang.ai in my business for a few months now and it's been great. It's especially useful in scenarios where I need to quickly process large amounts of data, such as customer surveys or sales reports. It can handle text, numbers and images really well. For more complex tasks like natural language processing, Lang.ai is also a great choice.

Incentivized

• Integration of IBM Watson APIs such as speech to text, image recognition, personality insights, etc.
• SPSS modeler and neural network model provide no-code environments for data scientists to build pipelines quickly.
• Enforced best-practices set up POCs for deployment in production with a minimum of re-work.
• Estimator validation lets data scientists test and prove different models.

Incentivized

• Great auto-tagging
• Improved tagging structure and system
• Efficient notes and organisation

Incentivized

• The cost is steep and so only companies with resources can afford it
• It will be nice to have Chinese versions so that Chinese engineers can also use it easily
• It takes a while to learn how to input different kinds of skin defects for detection

Incentivized

• More customization options when creating my own chatbot
• Better integration with other platforms like Slack
• The natural language processing accuracy could be improved to provide more accurate results in certain contexts.

Incentivized

because we find out that DSX results have improved our approach to the whole subject (data, models, procedures)

Incentivized

The UI flawlessly merges this offering by providing a neat, minimal, responsive interface

Incentivized

From time to time there are services unavailable, but we have been always informed before and they got back to work sooner than expected

Incentivized

Never had slow response even on our very busy network

Incentivized

I received answers mostly at once and got answered even further my question: they gave me interesting points of view and suggestion for deepening in the learning path

Incentivized

The trainers on the job are very smart with solutions and very able in teaching

Incentivized

The Platform is very handy and suggests further steps according my previous interests

Incentivized

It surprised us with unpredictable case of use and brand new points of view

Incentivized

The main reason I personally changed over from Azure ML Studio is because it lacked any support for significant custom modelling with packages and services such as TensorFlow, scikit-learn, Microsoft Cognitive Toolkit and Spark ML. IBM Watson Studio provides these services and does so in a well integrated and easy to use fashion making it a preferable service over the other services that I have personally used.

Incentivized

I recently compared Lang.ai with Glassbox, GetFeedback, and Watson Studio by IBM. I found that Lang.ai is the most comprehensive AI-based platform for automated customer feedback analysis. It has features like natural language processing, sentiment analysis, and emotion detection which are not available on the other platforms. Furthermore, Lang.ai's user interface is intuitive and easy to use, making it my top choice for automated customer feedback analysis.

Incentivized

It helped us in getting from 0 to DSX without getting lost

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• Could instantly show data driven insights to drive 20% incremental revenue over existing results
• Still don't have a real use case for unstructured data like twitter feed
• Some of the insights around user actions have driven new projects to automate mundane tasks

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• More time for customer service
• Addresses issues to prevent they occur again
• Identify priority of escalations

Incentivized