Sonata has leveraged its core capability to reimagine AI-first platforms, powered by its AI-enabled Modernisation Engineering Centre in India. Rajsekhar Datta Roy, CTO, Sonata Software, explains exclusively to Rajneesh De, Group Editor, CXO Media & APAC Media, that by combining cloud-native architectures with platform engineering and governed data layers, Sonata enables customers to deploy AI across connected systems while maintaining operational control.
What are the use cases for Sonata Software’s AI platforms like Harmoni.AI and AgentBridge?
 At Sonata Software, our AI platforms—Harmoni.AI and AgentBridge—are purpose-built to enable enterprises to deploy AI at scale with measurable business impact.
These platforms are designed around a responsible-first principle, ensuring AI systems can be safely operationalised in complex enterprise environments.
Our business process automation use cases come under three arrowheads:
- Business process transformation across functions such as Finance, HR, Legal, and Sales through a library of proprietary assets, intelligent automation, decision support, and knowledge systems.
- AI-led legacy modernisation, integrating AI into existing application landscapes.
- Reimagined customer experiences, powered by intelligent agents operating within strict guardrails for data privacy, security, and explainability.
Together, Harmoni.AI and AgentBridge help enterprises move from experimentation to production-grade AI adoption.
In platform engineering, AI, and data modernisation, what are Sonata’s key focus areas?
We have transformed all our core practices to be AI-first and responsible. A major focus area has been legacy modernisation, where AI is tightly coupled with platform engineering and data to enable modernisation.
Data modernisation underpins all these initiatives. We help enterprises modernise their data stacks by expanding data sources, incorporating vector databases, and enabling modern analytics and AI workloads. The objective is to improve business agility, allowing organisations to respond quickly to changing market conditions, while driving efficiency through modern, scalable data infrastructure.
In parallel, we have built industry-specific assets and accelerators, with a strong focus on platforms such as Microsoft Fabric, to speed up adoption and value realisation.
What are the principles behind Sonata’s responsible-first AI and Generative AI in action?
For us, responsible-first AI is about operational controls, not intent statements. Our Harmoni.AI platform embeds governance directly into the AI lifecycle.
This includes built-in mechanisms for:
- Role-based access control
- Data isolation
- Prompt and model governance
- Continuous model monitoring
- Regulatory compliance and human oversight
In Generative AI use cases, this ensures enterprises can control what data models have access to, how outputs are generated, and how those outputs are reviewed and used. Governance is designed into solutions from day one, rather than being retrofitted later. This is what enables Generative AI systems to move confidently into enterprise-grade production environments.
How many of Sonata’s current projects are in the Generative AI space and what are their use cases?
Today, we have more than 100 active engagements involving AI and Generative AI. The majority of these are production deployments, not exploratory pilots.
Key use cases include:
- AI-driven legacy application modernisation
- AI-enabled software engineering and testing
- Intelligent business process automation
Each engagement is anchored to specific business outcomes, ensuring AI adoption translates directly into operational and financial value.
What are the functions of Sonata’s dedicated AI-enabled Modernisation Engineering Centre in India?
Sonata has been a product engineering-led organisation for over two decades, building platforms and products at scale. We have leveraged this core capability to reimagine AI-first platforms, powered by our AI-enabled Modernisation Engineering Centre in India.
The centre supports end-to-end modern engineering, including:
- Requirements engineering, design, development, and testing
- AI-enabled legacy modernisation and platform transformation
- Managed services covering transition, incident management, observability, and security
This integrated model allows us to deliver modernisation programs with speed, quality, and enterprise-grade reliability.
How is Sonata training its workforce in the AI and Generative AI space?
Our workforce strategy is designed to support AI delivery at scale. We have launched the Sonata Modernisation Engineers (SME) program across the organisation, covering common AI fundamentals as well as practice-specific deep dives.
In addition, all enabling functions, beyond engineering, have undergone AI training to build organisation-wide fluency, including exposure to AI-first development and vibe coding practices.
We ensure all employees understand AI fundamentals so they can work effectively in AI-enabled environments. For engineers, the focus is on building, deploying, and operating AI systems responsibly in production.
How is Sonata leveraging cloud as the launchpad for its Connected Digital Business Platform?
We believe that enterprises must increasingly operate within ecosystems, and connected digital platforms are essential for enabling agile, non-linear growth. Sonata’s Platformation approach and accelerators are designed to make this possible.
Cloud ecosystems provide the agility and scalability required for this transformation. We have unified our cloud and AI practices into what we define as an AI Cloud, encompassing AI-ready infrastructure, security controls, and deep observability.
By combining cloud-native architectures with platform engineering and governed data layers, we enable customers to deploy AI across connected systems while maintaining operational control. This approach accelerates innovation without compromising enterprise stability.
How has Sonata powered AI-first ERP transformation in enterprises?
Our AI-first ERP approach is centred on transformation, not implementation.
We begin by reimagining business processes using design thinking to identify where AI can deliver the greatest impact. We then define a future-state AI architecture that supports responsible, scalable deployments across ERP environments.
This is complemented by pre-built assets and accelerators that speed up ERP service delivery, reduce risk, and enable continuous optimisation—resulting in ERP platforms that are intelligent, adaptive, and future-ready.
What are the key pillars of Sonata’s AI and GenAI go-to-market strategy?
Our AI and Generative AI go-to-market strategy is built on three execution priorities.
First, AI service is built on Sonata’s core capabilities of business process transformation, AI-led legacy modernisation, and reimagined customer experiences to deliver value upfront – moving from Responsible AI to ROI.
Second, we work closely with strategic partners such as Microsoft, Amazon Web Services and infrastructure providers to deliver scalable, production-ready AI solutions.
Third, we continually build differentiated capability in our area of focus, allowing sustained value creation.
