Engineering suite of "Intelligent Applications" for the enterprises

In the last few years, we have witnessed the proliferation of AI getting adopted in the enterprises to solve some of the critical problems. This is true and applicable across all the major industries - including - Finance, Insurance, Telecom, Healthcare, Entergy, Internet Services and the like. The most apparent outcome of this wave of change is that the traditional applications are now being disrupted and are getting replaced with "Intelligent Applications".

In this talk, we would explore what makes "intelligent Applications" different from the traditional application and what are the technical challenges in designing, architecting, deploying and maintaining such systems at the enterprise scale. The talk would cover some of the important details in designing the enterprise-wide suite of intelligent applications, some of the architectural considerations and design patterns, and the best practices.


Outline/Structure of the Talk

Welcome Remarks

Define intelligent applications

How are they different from traditional non-intelligent applications

Technical Challenges - What it takes to bring intelligence to applications

Architectural Considerations and Design Patterns.

Best Practices on designing, deploying and maintaining intelligent applications.

Tools, Technologies, and Frameworks that are emerged in the last few years to tackle these challenges


Closing Remarks

Learning Outcome

Understanding of what Intelligent Applications are, how best to design, build, deploy and manage them.

Target Audience

AI Engineers, Architects, and Data Scientists.

Prerequisites for Attendees

Prior knowledge in building products and exposure to machine learning is desired.

Prior knowledge of operationalizing machine learning systems would be good to have.

schedule Submitted 1 year ago

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