Cloud
Analytics
Artificial intelligence
December 5, 2022 By Omkar Nimbalkar 3 min read

IBM has invested $1 billion into our partner ecosystem. We want to ensure that partners like you have the resources to build your business and develop software for your customers using IBM’s industry-defining hybrid cloud and AI platform. Together, we build and sell powerful solutions that elevate our clients’ businesses through digital transformation.

To that end, IBM recently announced a set of embeddable AI libraries that empower partners to create new AI solutions. In fact, IBM supports an easy and fast way to embed and adopt IBM AI technologies through the new Digital Self-Serve Co-Create Experience (DSCE).

The Build Lab team created the DSCE to complement its high-touch engagement process and provide a digital self-service experience that scales to tens of thousands of Independent Software Vendors (ISVs) adopting IBM’s embeddable AI. Using the DSCE self-serve portal, partners can discover and try the recently launched IBM embeddable AI portfolio of IBM Watson Libraries, IBM Watson APIs, and IBM applications at their own pace and on their schedule. In addition, DSCE’s digitally guided experience enables partners to effortlessly package and deploy their software at scale.

Your on-ramp to embeddable AI from IBM

The IBM Build Lab team collaborates with qualified ISVs to build Proofs of Experience (PoX) demonstrating the value of combining the best of IBM Hybrid Cloud and AI technology to create innovative solutions and deliver unique market value.

DSCE is a wizard-driven experience. Users respond to contextual questions and get suggested prescriptive assets, education, and trials while rapidly integrating IBM technology into products. Rather than manually searching IBM websites and repositories for potentially relevant information and resources, DSCE does the legwork for you, providing assets, education, and trial resources based on your development intent. The DSCE guided path directs you to reference architectures, tutorials, best practices, boilerplate code, and interactive sandboxes for a customized roadmap with assets and education to speed your adoption of IBM AI.

Embark on a task-based journey

DSCE works seamlessly for both data scientist and machine learning operations (ML-Ops) engineers’ personas.

For example, data scientist, Miles wants to customize an emotion classification model to discover what makes customers happiest. His startup provides analysis of customer feedback to help the retail e-commerce customers it serves. He wants to provide high-quality analysis of the most satisfied customers, so he chooses a Watson NLP emotion classification model that he can fine-tune using an algorithm that predicts ‘happiness’ with greater confidence than pre-trained models. This type of modeling can all be done in just a few simple clicks:

  • Go to https://dsce.ibm.com ->
  • Find and try AI ->
  • Build with AI Libraries ->
  • Build with Watson NLP ->
  • Emotion classification ->
  • Library and container ->
  • Custom train the model ->
  • Results Page

The bookmarkable Results Page gives a comprehensive set of assets for both training and deploying a model. For accomplishing the task of “Training the Model,” Miles can explore interactive demos, reserve a Watson Studio environment, copy a snippet from a Jupyter notebook, and much more.

If Miles, or his ML-Ops counterpart, Leena, wants to “Deploy the Model,” they can get access to the trial license and container of the new Watson NLP Library for 180 days. From there it’s easy to package and deploy the solution on Kubernetes, Red Hat OpenShift, AWS Fargate, or IBM Code Engine. It’s that simple!

Try embeddable AI now

Try the experience here: https://dsce.ibm.com/ and accelerate your AI-enabled innovation now. DSCE will be extended to include more IBM embeddable offerings, satisfying modern developer preferences for digital and self-serve experiences, while helping thousands of ISVs innovate rapidly and concurrently. If you want to provide any feedback on the experience, get in touch through the “Contact us” link on your customized results page.

Additional resources

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Omkar Nimbalkar
Vice President, Ecosystem Engineering - WW Build Lab and Red Hat Marketplace

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