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IBM Data and AI Ideas Portal for Customers

Shape the future of IBM!

We invite you to shape the future of IBM, including product roadmaps, by submitting ideas that matter to you the most. Here's how it works:

Post your ideas

Post ideas and requests to enhance a product or service. Take a look at ideas others have posted and upvote them if they matter to you,

  1. Post an idea

  2. Upvote ideas that matter most to you

  3. Get feedback from the IBM team to refine your idea

Help IBM prioritize your ideas and requests

The IBM team may need your help to refine the ideas so they may ask for more information or feedback. The product management team will then decide if they can begin working on your idea. If they can start during the next development cycle, they will put the idea on the priority list. Each team at IBM works on a different schedule, where some ideas can be implemented right away, others may be placed on a different schedule.

Receive notification on the decision

Some ideas can be implemented at IBM, while others may not fit within the development plans for the product. In either case, the team will let you know as soon as possible. In some cases, we may be able to find alternatives for ideas which cannot be implemented in a reasonable time.

Additional Information

To view our roadmaps:

Reminder: This is not the place to submit defects or support needs, please use normal support channel for these cases

IBM Employees:

The correct URL for entering your ideas is:



Natural Language Understanding (NLU)

Showing 2

Improve German sentiment classifier!

The sentiment classifier is not suitable for German documents. Nearly 90% of all the documents in the news-de collection in watson-discovery are classified "neutral". If I use other classifier-services I get tremendously different percentages. (e....
over 3 years ago in Natural Language Understanding (NLU) 0 Delivered

Return the start/end indexes of an entity mention in the text.

When predicting entities in a document, the NLU Service does not return any information about where the entities were found in the text. Since we use custom models with a lot of numerical entities, it becomes very hard to find the sentences where ...
almost 5 years ago in Natural Language Understanding (NLU) 1 Delivered