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Transforming Legacy Systems with Generative AI for Smart Sustenance
Transforming Legacy Systems with Generative AI for Smart Sustenance

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Legacy systems remain critical to the IT landscape of many organizations. However, as these systems approach the end of their lifecycle, companies face the challenge of updating, upgrading, or modernizing them to maintain exceptional customer service. Yet, this process often consumes significant engineering bandwidth, leading to higher costs and diverting focus from new product development.

In today’s fast-paced market, traditional sustenance engineering approaches fall short. Organizations need to harness the transformative power of Generative AI (GenAI) to overcome knowledge barriers, expedite code reviews, and streamline workflows.

Discover how GenAI can revolutionize software product sustenance and enable smarter application support and engineering.

Understanding Software Product Sustenance and Support

Legacy systems, while integral to modern IT ecosystems, demand ongoing maintenance and support. Software product sustenance solutions tackle challenges posed by older technologies, revitalizing these systems and extending their value and lifespan. By addressing bug fixes, implementing new features, upgrading technology, and improving UI/UX, product sustenance engineering ensures legacy systems stay relevant in dynamic markets.

Robust software sustenance and support deliver continuous product relevance. This includes:

  • Extending product lifecycles: Adding features and fixes ensures software remains effective.

  • Building migration roadmaps: Planning for next-gen platform transitions.

  • Managing product end-of-life: Offering comprehensive L1-L4 customer support.

  • Reducing backlog: Resolving dormant tickets, often requiring customer engagement.

The Power of GenAI in Smart Sustenance Solutions

GenAI brings unprecedented efficiency to sustenance engineering. By enabling automation, collaboration, and problem-solving, it reduces the engineering effort required for end-of-life products while maintaining top-tier customer service.

Key Benefits of GenAI-Powered Sustenance:

  • Cost Minimization: GenAI enables hyperautomation in code building, testing, and releasing. Automated test code generation across unit, functional, regression, and integration testing reduces modernization costs. Additionally, GenAI’s maintenance and document generation automation allow teams to allocate resources to new product development.

  • Enhanced Serviceability: With NLP-enabled observability assistants, support teams receive insights to improve application performance. Intelligent RunOps capabilities automate issue resolution, ensuring smooth operations.

  • Faster Defect Resolution: GenAI accelerates issue resolution by mining error databases and providing instant answers to known problems. Proactive error detection, log monitoring, and automated code reviews further enhance accuracy and efficiency.

  • Reduced Technical Debt: GenAI models identify code pitfalls and automate corrections, accelerating development timelines. Automated testing tools improve code robustness, reducing the risk of new bugs.

Advanced Sustenance Engineering with AI-Driven Insights

Integrating AI into sustenance engineering optimizes efficiency, reduces costs, and enhances decision-making. Organizations can:

  • Design optimized products and simulate scenarios.

  • Predict maintenance needs by analyzing performance data.

  • Use NLP to analyze customer feedback and sentiment.

  • Personalize user experiences and tailor product features.

  • Provide 24/7 support via AI-driven chatbots.

  • Make data-driven decisions for continuous product improvements

Customizing Product Sustenance Solutions

Effective product sustenance requires flexibility and adaptability to specific market and product needs. AI-driven strategies enable organizations to:

  • Predict defects using historical patterns.

  • Develop tailored algorithms for unique maintenance needs.

  • Create predictive models addressing distinct failure modes.

  • Train machine learning models on product-specific data.

  • Test modernized applications in real-world scenarios.

  • Build custom dashboards offering real-time performance insights.

Success Stories: AI-Powered Sustenance in Action

Business Need: A global procurement software provider faced challenges managing a surge of customers post-merger. The internal team struggled with bug resolution, impacting customer satisfaction.

Solution: Xoriant implemented a GenAI-enabled sustenance model with over 100 engineers. The team delivered end-to-end sustenance services, feature enhancements, and streamlined processes across core modules like contract management and invoicing.

Business Benefits:

  • Reduced defect resolution time by 40%.

  • Improved CSAT from 4.0 to 4.5.

  • Accelerated delivery of new features.

Choosing the Right Partner for Sustenance Support Services

When selecting a partner for smart sustenance support, consider the following:

  • GenAI-First Approach: Ensure they leverage GenAI for continuous efficiency improvements.

  • Aligned KPIs and SLAs: Verify their metrics align with your goals.

  • Disruption and Cost Savings: Choose a partner who prioritizes innovation and cost reduction.

  • Industrialized Playbook: Opt for a partner with a proven transition model.

  • Outcome-Based Support: Look for risk-reward models offering upfront savings.

In Conclusion

As technology evolves, modernizing legacy systems is essential for maintaining relevance. GenAI-enabled sustenance engineering reduces engineering burden, extends product lifecycles, and redirects resources to innovation.

With expertise in product modernization, architecture transformation, and cloud migration, Xoriant’s GenAI-first approach ensures seamless sustenance engineering, delivering value-driven results aligned with committed KPIs.

 

Authored by:  Sandeep Raje - Associate Vice President of Delivery, Xoriant

Author Bio:

Sandeep Raje is the Associate Vice President of Delivery at Xoriant. He has extensive experience in financial services and product engineering as a results-oriented and high-energy global business and technology leader. With a proven track record in delivering complex, multi-tower transformation programs, Sandeep employs a hands-on approach to drive strategy, architecture, and implementation of innovative and cost-effective solutions. He has experience managing large portfolio budgets with meticulous attention to detail.


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Xoriant is a Silicon Valley-headquartered digital product engineering, software development, and technology services firm with offices in the USA,UK, Ireland, Mexico, Canada and Asia. From startups to the Fortune 100, we deliver innovative solutions, accelerating time to market and ensuring our clients' competitiveness in industries like BFSI, High Tech, Healthcare, Manufacturing and Retail. Across all our technology focus areas-digital product engineering, DevOps, cloud, infrastructure, and security, big data and analytics, data engineering, management and governance -every solution we develop benefits from our product engineering pedigree. It also includes successful methodologies, framework components, and accelerators for rapidly solving important client challenges. For 30 years and counting, we have taken great pride in our long-lasting, deep relationships with our clients.

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