Agivant’s Solution Framework for Integrating the Enterprise Level Machine Learning Models with Adobe Experience Platform and CDP For Hyper Personalized, Intelligent, and Real-Time Solutions.
Hyper-personalized, intelligent, and real-time solutions are necessary for every enterprise to understand and analyze their end-customer needs in real-time and respond with the most relevant insights for creating positive and high-impact end-customer expectations.

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Such hyper-personalized, intelligent, and real-time solutions require a combination of various technical solutions to gather, process, and analyze data quickly, efficiently and integrate with multiple channels seamlessly.
Agivant’s AI-First Cloud and Digital Engineering Lab has built the solution framework by leveraging Adobe Experience Platform solutions to the existing enterprise-level Machine Learning models with integration into enterprise systems.
The comprehensive solution framework covers the in-depth approach to integrating various solution components:
  • Customer data platform (CDP)
  • Real-time data ingestion and stream processing platforms
  • Machine learning models
  • Real-time decision engine, Real-time analytics & monitoring frameworks
  • Privacy and Security
  • Integration of the real-time decision outputs on various channels – websites, portals, mobile applications, chatbots, commerce sites, social media solutions, call centers, self-service solutions, kiosks, etc.
 
Adobe Experience Platform, Adobe’s real-time customer data platform, enables the collection, organization, and activation of customer data across multiple channels and provides the integration capabilities with existing machine learning models through its various integration services and integrates with other Adobe marketing tools, providing a comprehensive solution for customer data management and personalization.
Agivant’s solution covers the following high-level steps to integrate the existing machine learning models with Adobe’s real-time CDP and Adobe Experience Platform:

Build and export the Machine learning models in industry-standard formats such as Predictive Model Markup Language or Open Neural Network Exchange.

Establish Data Flow between Adobe Experience Platform and the environment for executing machine learning models.

You can seamlessly integrate the Adobe Experience Platform with the model execution environment using real-time APIs or connectors.

Execute the Machine learning models and leverage the model outputs in Adobe Experience Platform.

Integrate real-time outputs with Adobe marketing tools to deliver personalized content across various channels.

Solution Architecture for custom Data Science model for Profile Enrichment

By leveraging the solution approach, it is possible to integrate a range of machine learning models, including Real-time Personalization, Predictive Analytics, Customer Segmentation, Anomaly Detection, Product Recommendations, and Churn Prediction. with the Adobe Experience Platform. Some business use cases include Real-Time Content Personalization, Real-Time Pricing and Offers, Real-Time Recommendations, Real-Time Customer Service, Real-Time Fraud Detection, Real-Time Personalized Experiences, and Real-Time Ad Targeting.
Value to Customer: Agivant’s data scientists and Adobe experts have rich industry experience in building machine learning models based on various business use cases and integrating those models with Adobe Experience Platform and CDP in real-time to deliver hyper-personalized and intelligent engagements with end-customers across channels.
Agivant’s solution framework can be implemented for multiple business use cases across industries to differentiate the enterprises for servicing their end-customers, resulting into
  • Better acquisition rates – 20% to 40% increase
  • Higher retention by engaging at the right time on the proper channels – 25% improvement
  • Improved customer satisfaction
  • Faster business growth through digital channels at lower costs
  • Faster adoption of CDP, real-time decision engine, and marketing tools – 20% saving
Engagement Model: We partner to design the customized solution approach with a 6 to 8 weeks consulting program with our clients. We follow an agile approach to roll out business use cases in a phased manner to start delivering business outputs starting at earlier stages.
Agivant Lab leverages our solution framework to deliver CDP, real-time decision engine, machine learning models, and Adobe marketing tools.

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DevOps Engineer

Industry experience: 10 Years
Location: Pune

To apply for this opportunity, write to us at careers@agivant.com with the following subject: AG5111-DevOps Engineer

Agivant is a new-age AI-First Digital and Cloud Engineering services company that drives Agility and Relevance for our client's success.

Powered by cutting-edge technology solutions that enable new business models and revenue streams, we help our customers achieve their trajectory of growth.

Agility is a core muscle, an integral part of the fabric of a modern enterprise.

To succeed in an ever-changing business environment, every modern organization needs to adapt and renew itself quickly. We help foster a more agile approach to business to reconfigure strategy, structure, and processes to achieve more growth and drive greater efficiencies.

Relevance is timeless, and is the only way to survive, and to thrive.

The quest for relevance defines the exponential acceleration of humanity. This has presented us with a slew of opportunities, but also many unprecedented challenges. With technology-led innovation, we help our customers harness these opportunities and address the myriad challenges.