Digital Terminal brings this exclusive interview with Nitish Shrivastava, Senior Vice President and Head of Product Business at Persistent Systems. We'll delve into how Generative AI is transforming enterprise operations, the innovative capabilities of Persistent's SASVA platform, their commitment to ethical AI, and the power of strategic hyperscaler partnerships. Join us as we explore the future of AI-driven enterprise transformation.
DT: How do you see Generative AI reshaping enterprise operations in the near future, and what are the key challenges in integrating it at scale?
Nitish: AI is charting the future of modern enterprises, ushering in a new era of operational excellence and chalking new pathways for growth and value creation. GenAI, in particular, is enabling intelligent automation and faster decision-making, becoming a key driver for enterprise transformation. At Persistent, we are harnessing this momentum through purpose-built platforms that combine generative and deterministic AI to deliver tangible business outcomes. For example, SASVA, our Digital Engineering platform, enhances productivity, reduces technical debt, and accelerates time-to-market across industries.
However, enterprise-wide adoption of AI comes with a distinct set of challenges. Businesses are progressing cautiously while transitioning from isolated pilot projects to full-scale, integrated implementations. In a complex data-driven environment, managing voluminous data, its quality, governance, and associated costs remains a key barrier.
Further compounding the issue are data silos, legacy systems, and fragmented infrastructures that obstruct the path to AI effectiveness. Extracting actionable insights, ensuring data integrity, and automating migration processes require specialized capabilities. For instance, we addressed this for a leading networking and IT customer, accelerating test case migration with GenAI-powered solutions, achieving 95% accuracy, 1.5x faster migration, and 40% cost savings, demonstrating our efficacy in large-scale modernization efforts.
As organizations pursue speed, scalability, efficiency, cost optimization, and profitability, maintaining ethical AI practices becomes increasingly complex. Responsible AI must, therefore, be embedded into the very DNA of digital solutions. Learning and Development also plays a crucial role in this transformation because AI is a powerful engine that can be either a blessing or a curse, depending on how it is used and adopted. Tools like Vibe Coding, for instance, enable users to generate millions of lines of code within minutes to build applications. But with that power comes the responsibility to understand, maintain, and govern the code effectively. AI delivers value only when we use it thoughtfully, and that begins with robust training. Continuous upskilling and reskilling are essential to prepare teams, foster AI readiness, and ensure enterprise AI adoption is both successful and responsible.
DT: How does SASVA give Persistent a competitive edge in AI-driven software development, and how is it helping businesses scale AI while managing costs and complexity?
Nitish: At Persistent, we are reimagining the future of software development through the transformative power of AI. Our next-generation platform, SASVA, is custom-engineered to accelerate organization-wide AI adoption, embedding quality, governance, and scalability into every phase of the software lifecycle.
SASVA stands out for its ability to integrate deterministic algorithms with generative AI models, enabling the automation of routine tasks and infusing intelligence into every layer of the development process. Features like OSS Remediation Factory for automated open-source vulnerability management and AI-powered support workflows (L0 to L3), simplify complexity, mitigate risk, and boost developer productivity.
The platform enables hyper-personalization by training its models on enterprise-specific data, allowing insights, recommendations, and actions to be context-aware and relevant. This approach upholds quality standards, minimizes bias and hallucinations, and effectively addresses data sensitivity concerns.
The architectural flexibility—optimized for both CPU and GPU environments, drives cost efficiency while automating critical functions such as backlog management, security patching, and deployment workflows. For instance, SASVA reduced costs by 48% and increased team efficiency by 50% for an AI-powered supply chain platform while also enhancing business and addressing critical and high-security vulnerabilities for a leading wellness services platform.
Beyond individual outcomes, SASVA is gaining traction across enterprise-wide programs, from core product transformation and tech stack modernization to language upgrades and automated bug fixes. With 35 patents filed to date and continuous investments in new features, SASVA is more than a platform; it’s a strategic enabler that empowers clients to build and deliver modern, scalable software.
DT: Trust is often cited as a barrier to AI adoption. What steps is Persistent taking to ensure AI solutions are ethical, secure, and transparent?
Nitish: Organizations that lead with responsibility, safeguard trust, and innovate with intention will not only seize emerging opportunities but also establish the blueprint for a sustainable and resilient future. In fact, a BCG study reveals that approximately 70% of challenges in implementing AI initiatives stem from people and process-related issues, pressing the need for robust governance. At Persistent, we believe trust must be architected into every layer of AI deployment. Our Responsible AI Council leads from the front, ensuring AI deployments align with industry best practices, regulatory mandates, global standards, and principles of fairness, bias mitigation, and explainability.
To further institutionalize transparency and security, we embed these principles into our platforms, such as SASVA, iAURA, and the GenAI Hub, enabling responsible innovation at scale. With built-in safeguards that comply with global data protection standards like GDPR and HIPAA, we ensure privacy without compromising agility. For us, trust is not an afterthought; it is the foundation of every AI-driven transformation we deliver. By building AI with integrity, we are helping enterprises scale responsibly and sustain long-term impact.
DT: How are Persistent’s strategic partnerships with hyperscalers enabling faster and more efficient AI deployment?
Nitish: At Persistent, our collaborations are the force multiplier that positions us as the ‘Ecosystem Orchestrator of Choice’ for our clients. Our partnerships with hyperscalers and broader technology providers, including AWS, Google Cloud, Microsoft, Salesforce, Databricks, and Snowflake, serve as engines of co-innovation. Together, we’re building industry-specific AI solutions that tackle real-world challenges head-on.
These partnerships enable us to move with speed, precision, and purpose.
Accelerate time-to-market by leveraging pre-built, optimized cloud services, and AI models from hyperscaler platforms, minimizing custom development efforts.
Enhance scalability and agility by tapping into hyperscalers’ robust cloud environments, making it easy to scale AI workloads securely and efficiently.
Improve cost efficiency through flexible pricing models and by accessing cutting-edge AI technologies without significant upfront infrastructure investments.
Leverage advanced AI tools like machine learning frameworks, data lakes, and pre-trained models to enable faster development cycles and more precise outcomes.
Our "Customer Zero Implementation" approach ensures that every AI solution we offer is first validated internally, minimizing risk and ensuring readiness before customer deployment. This internal-first strategy builds confidence and accelerates adoption at scale.
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