AiThority Interview with Dr. Rajesh Gharpure, Chief Delivery Officer at Persistent Systems

Dr. Rajesh Gharpure, Chief Delivery Officer at Persistent Systems chats about the latest data analytics and AI trends in the delivery process, concerns around cybersecurity and data privacy, best practices to build a robust enterprise IT security framework and more in this Q&A:

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As a thought leader in digital transformation, how do you see trends such as AI, automation, and cloud adoption evolving over the next 2-3 years, particularly in the Banking, Financial Services, and Insurance sectors?

In recent years, AI, automation, and cloud adoption have emerged as essential drivers of business transformation, enabling organizations to enhance operational efficiency, deliver hyper-personalized experiences, and achieve greater agility. In the BFSI sector, these technologies are fostering innovation in customer engagement, streamlining operations, and strengthening risk management.

AI and automation are improving efficiency and customer experiences. For instance, Persistent’s Digital Banking Studio empowers financial institutions to create intuitive, AI-driven customer interactions. At the same time, advanced tools optimize processes like loan origination and claims management, significantly reducing errors and improving turnaround times.

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Digital lending is another area experiencing rapid transformation. Persistent’s Digital Lending solutions integrate AI to streamline every step of the lending process, from application to approval. These solutions reduce operational costs, ensure transparency, enable faster decision-making, enhance efficiency, and build customer trust in a competitive market.

AI is also reshaping fraud detection and credit risk management. Persistent’s platforms enable real-time anomaly detection and more accurate credit decisions, reducing risks and non-performing assets. Additionally, digital-native banks, built on cloud-first principles, are leveraging AI to attract younger, tech-savvy customers, achieving rapid growth and market share.

These advancements are reshaping the BFSI landscape, offering institutions opportunities to innovate while meeting the challenges of trust, governance, and compliance.

How is Persistent leveraging data analytics and AI to enhance its service delivery and operational efficiency? Could you provide examples of how these technologies are being integrated into your delivery processes?

At Persistent, leveraging data analytics and AI is foundational to driving operational efficiency and delivering measurable outcomes. Our focus is on embedding intelligence into our processes through our innovative platforms like iAURA and SASVA, which have been designed to solve complex challenges at scale.

iAURA automates large-scale data and reporting migrations while ensuring data integrity, robust governance, and cost optimization, making it a game-changer for organizations modernizing their data ecosystems. A leading BFSI company faced the challenge of migrating thousands of legacy reports to a modern platform. Traditional methods would have required significant time and resources. Using iAURA, we automated 60% of the migration process, dramatically reducing effort and costs while ensuring the data met accuracy and improved compliance standards.

SASVA enhances our software delivery lifecycle by integrating AI-driven capabilities. From AI-assisted coding and release management to real-time analytics, it enables smarter decision-making and faster outcomes. We recently helped a client automate their data infrastructure setup, reducing project timelines by weeks without compromising quality.

This combination of advanced data analytics and AI enables us to work predictably, efficiently, and at scale. It’s not just about improving delivery speed—it’s about consistently exceeding client expectations by embedding intelligence into every stage of our operations.

With increasing concerns around cybersecurity and data privacy, how is Persistent addressing enterprise IT security to protect both its clients and internal operations?

Cybersecurity is a top priority at Persistent, and we approach it with a strong focus on resilience, adaptability, and trust. Our framework combines proactive and predictive measures, advanced technologies, and robust governance to safeguard both internal systems and client engagements using prescriptive playbooks and runbooks for response and recovery.

Our Zero Trust Architecture and Framework enforces strict authentication and authorization for all access to sensitive data. Additionally, our next-generation Cyber Fusion Center (CFC) integrates automated threat intelligence, threat hunting, and predictive capabilities to proactively identify vulnerabilities and mitigate risks before they escalate. Regular audits, penetration testing, and tabletop exercises further strengthen our readiness for potential incidents with detailed runbooks to respond and recover from incidents if the need arise.

Employee awareness is another critical focus. Continued on-the-job training and simulation exercises equip our teams to recognize and respond to threats such as phishing and social engineering. Transparency with clients is also key—we conduct independent audits when required and ensure all data handling adheres to global security and privacy regulations.

To enhance our capabilities further, we recently acquired Arrka, a company renowned for its decade-long data privacy expertise. This acquisition enables us to seamlessly integrate compliance, ethics, and governance into our AI-driven services, empowering clients to innovate responsibly and manage risks effectively.

By prioritizing trust, transparency, and robust measures, we help our clients confidently navigate today’s evolving threat landscape.

What are some best practices that organizations can adopt to build a robust enterprise IT security framework, especially in a multi-cloud environment?

Building a strong IT security framework in a multi-cloud environment requires a combination of strategic planning, consistent policies, and advanced tools. Some best practices include:

1. Ensure Basic Security Hygiene: Establish clear patching and vulnerability review and mitigation practices. Implement robust account security with strong password policies complimented with multi-factor authentication.
2. Unified Cloud Security Policies: Establish consistent policies across all cloud platforms while tailoring specific policies for individual cloud service providers. This ensures alignment with organizational security goals while addressing unique platform risks.
3. Centralized Monitoring and Management: Use tools that provide unified visibility, management, and threat detection across multiple cloud environments. Solutions that support multi-cloud natively or through third-party integrations can streamline this process effectively.
4. Single Identity Provider with Role-Based Access Control: A single identity provider simplifies access control while enabling granular role-based policies to restrict data access to authorized users only.
5. Regular Security Audits and Vulnerability Assessments: Periodic or real-time assessments help identify weaknesses in the cloud environment, allowing organizations to maintain a strong security posture and address issues proactively.
6. Incident Response Plans: Incident response plans should be regularly updated to reflect the dynamic nature of cloud environments. These plans should cover all aspects—from detection and containment to recovery—to ensure rapid and effective responses to security incidents.
7. Endpoint Security and AI-Driven Access Management: Implementing endpoint protection, user-level controls, and AI-driven policies ensures data confidentiality by dynamically assessing content and determining the appropriate level of security without disrupting the user experience.
8. Move from Cybersecurity to Cyber Resilience: Create robust runbooks supported by integrated threat defense and automated response playbooks to shift mindset from cybersecurity to cyber resiliency. Perform periodic planned and unplanned simulations and assessments to review the preparedness and effectiveness of cyber resiliency efforts.

By adopting these practices, organizations can create a robust, adaptable IT security framework that addresses the complexities of operating in multi-cloud environments while maintaining agility and compliance.

What are your top priorities for Persistent in the coming year? Are there any new service lines or innovative solutions that you’re particularly excited about?

At Persistent, our priorities for the coming year are centered around driving innovation, amplifying talent, and delivering measurable outcomes for our clients. As an AI-first, platform-driven services company, we’re focused on creating high-impact solutions that address the evolving needs of our clients while positioning ourselves as the ecosystem orchestrator of choice in the industry.

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A key focus is talent amplification—empowering our teams with advanced tools, comprehensive training, and opportunities to deliver expert services. By equipping our workforce with cutting-edge AI and platform capabilities, we aim to maximize client ROI, foster innovation, and build long-term partnerships.

We’re also strengthening our role within the partner ecosystem. Collaboration is key to delivering end-to-end, disruptive solutions that address complex business challenges. By becoming the orchestrator of choice, we enable clients to seamlessly adopt innovative technologies that drive real-world impact.

On the innovation front, we’re particularly excited about our GenAI Delivery service. This offering allows clients to unlock the full potential of GenAI by improving decision-making, creating intelligent workflows, and enabling smarter automation. It’s helping businesses stay ahead in a landscape that’s evolving faster than ever.

We’re also advancing our flagship platforms, including the launch of SASVA 2.0, the latest iteration of our AI-powered platform revolutionizing software engineering with generative and deterministic AI. SASVA 2.0 redefines delivery through intelligent backlog management, enhanced project assessments, and AI-augmented development processes. Meanwhile, the iAURA suite streamlines data migration, ensures data quality, and empowers organizations to turn raw data into actionable insights.

These priorities reflect our commitment to pushing boundaries and helping clients navigate the complexities of digital transformation with confidence and agility. We believe these efforts will further cement Persistent’s position as a leader in the industry.

 Quick Insights:

• One technology trend you’re excited about in 2025.

In 2025, the incorporation of AI into software engineering and business processes will be transformative. On the technology side, AI-driven platforms are enabling smarter, more efficient software development. By leveraging historical data and market insights, these tools can intelligently manage backlogs, optimize resource allocation, and streamline release planning. This shift is helping organizations accelerate time-to-market while maintaining high quality and reducing costs.

On the business front, AI is evolving beyond traditional analytics to create actionable intelligence. Platforms integrating AI, like those used in industries such as pharmaceuticals and construction, are driving unprecedented efficiencies. For example, AI is accelerating drug discovery by connecting complex biomedical datasets and optimizing clinical trial management through real-time insights. In construction, AI models are using historical data to guide decisions for ongoing and future projects, improving outcomes and reducing delays.

• A book or podcast you’d recommend to tech leaders.
  • Podcast: Data Engineering Podcast by Tobias Macey – A fantastic resource for understanding modern data challenges and solutions.
  • Book: Nexus: A Brief History of Information Networks from the Stone Age to AI – Offers a fascinating perspective on the evolution of information systems and their impact on technology and society.
• If you could instantly solve one tech challenge, what would it be?

The data quality challenge—eliminating issues around bad, incomplete, or outdated data—would be my choice. Quality data is the cornerstone of trust in AI-driven decisions, yet many organizations struggle with inconsistent, fragmented, or mismatched datasets. Problems like schema drift, incomplete data ingestion, and outdated records severely limit AI’s ability to learn effectively and predict outcomes accurately. This leads to poor business decisions, operational inefficiencies, compliance risks, and diminished confidence in data-driven strategies.

At Persistent, we’ve addressed this challenge through our iAURA platform, which ensures impeccable data quality by automating key processes:

• AI-driven data profiling identifies anomalies and recommends rules to standardize data.
• A rule recommendation engine and comprehensive rule library enforce quality measures across platforms.
• Data quality scoring and dashboards provide actionable insights into data health.

By tackling data quality at its root, Persistent enables businesses to unlock AI’s full potential, delivering smarter decisions, accurate predictions, and stronger business outcomes.

Thank you, Dr. Rajesh, for sharing your insights with us.

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