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AI Product Development Services for Analytics and Digital Twins

AI Product Development and Engineering for Analytics and Digital Twins

AI Engineering for driving value within Systems by developing tools, systems, and processes for DigitalOps and Digital Twin. Enabling AI Insights with Data Intelligence to create new service models that delight customers and improve performance.

XenonStack Digital Product Strategy

DevSecOps 

Digital Transformation towards autonomous operations by integrating different products and business processes for real-time insights and decision-making.

XenonStack Product Modernization

DataOps 

Modernising products to drive business value needs a Cloud Platform strategy for data and application modernisation for automation and Generative AI 

XenonStack Product Experience Design

ModelOps 

During Modernization or building a new digital product, enterprises need service design to map customer requirements and redefine user journeys 

AI Product Engineering with Cloud Native 

For Rapid Software product development and faster delivery, incorporating accelerator solutions to reduce the SDLC lifecycle and provide faster time to market.

XenonStack Product Engineering Wheel

Increase Operational Scale with AI ecosystems

XenonStack Product Sustenance & Support

Sustenance and Support

Maintaining and sustaining legacy applications for customer revenues at reduced cost with defined SLAs while transitioning to new modern architectures.

XenonStack Product Sustenance & Support

Incorporating Service Design principles empowers businesses to streamline New User Experience design and simplify software operations.

API driven Architecture helps enterprises to adopt platforms, ensure better resiliency and increase stability.

Implementing Continuous Integration and Delivery best practices is essential for developing faster software release cycles and enabling automated software development life cycles.

Leveraging TestOps and Test Automation based capabilities for efficient management of software testing processes and developing optimized Test Strategy.

AI Software Product Engineering Services 

AI Digital Product development Services and Strategy Consulting for streamlining and accelerating development.

Advanced Product Engineering Solutions for Building Human-centered AI Applications

Product Design needs human centered approach for ethical AI implementations.

AI Product Engineering for Data-Centric, Collaborative and Value Sensitive Designing

Integrating Design with Technology needs systematic approach for human Values

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Enterprise Technology

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Banking and Finance Sector

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Healthcare

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Education

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Transportation

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Retail

Key Enablers

Enablers for Accelerating Digital Transformation

XenonStack  Big Data Engineering

Enterprise AI

XenonStack Data Science

Big Data Engineering

XenonStack DevOps

Generative AI

XenonStack Enterprise AI

DevOps

XenonStack Serverless

Data Science

XenonStack Data Visualization

Data Visualization

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Featured Product Engineering Insights

What are the various stages of Product Testing?

product-testing-process

What are the various stages of Product Testing?

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A Quick Guide to streamlining User Experience in Software Development

A Quick Guide to streamlining User Experience in Software Development

Overview of Product Management Roadmap

Product Management Roadmap

Overview of Product Management Roadmap

Product Design

Data as a Product

Digital Platform Strategy

Platform-as-a-Service

Product Design

Product Design Service offerings for User Experience and Interaction Design, User Experience Strategy Consulting.

Metadata - Data as a product

Metadata is the data for the data, and metadata enriches the data with information, making data discovery, use, and management more accessible. There is a variety of metadata depending on the use-cases, i.e., purpose, format, quality, and volume.

Building an integrated Digital Platform strategy empowers businesses to drive interconnected ecosystems with microservices architecture for digital transformation.

Platform-as-a-Service

Overview of What are the Challenges and Best Practices of building Platform-as-a-Service applications.