Satyajit Saha has helped turn GenAI from an experimental capability into a core growth engine for Evalueserve. GenAI offerings now contribute 25% of overall revenue, are growing 45% year on year, and support dozens of Fortune 500 clients, while Satyajit leads approximately 200 technology, product, and AI professionals taking AI into production at scale.
For many organisations, the challenge with GenAI is turning experimentation into sustained adoption and measurable business value. That transition has defined Satyajit’s leadership at Evalueserve.
Leading the company’s technology, digital products, and GenAI strategy, Satyajit has built an operating model designed to move AI beyond individual proofs of concept and into repeatable products, client workflows, and everyday delivery.
Starting Transformation from Within
Rather than beginning with external propositions, Satyajit first focused on making AI accessible within Evalueserve itself. He led the development of Genie, the internal agentic AI platform, opening access to business users and enabling non-technical employees to create their own AI agents. The aim was to develop a citizen-developer culture in which teams could identify opportunities and integrate AI into their workflows without depending on central technical functions.
That internal experience subsequently became a foundation for client-facing agentic AI platforms, reusable accelerators, and domain-specific applications. The commercial results demonstrate how far that strategy has progressed:
- GenAI now contributes 25% of Evalueserve’s overall revenue.
- GenAI-related revenue has grown 45% year on year.
- Evalueserve supports 25–30 Fortune 500 clients on GenAI programmes.
- 90% of those clients continue into a second year.
- AI-assisted and automated delivery is used across 70–85% of data engineering engagements.
The emphasis throughout has been on integrating AI into real workflows rather than treating deployment itself as the measure of success.
“Satyajit has proven himself to be a powerhouse of commercialisation, driving Generative AI initiatives to account for a staggering 25% of overall corporate revenue with a 45% YoY growth rate. By building ‘Genie’, he established a democratic citizen-developer culture internally before successfully deploying high-value agentic AI solutions for major global clients” – Judges’ comments
Building an Organisation Around AI
Satyajit leads around 200 professionals across technology, product, AI, engineering, data science, and domain consulting.
His approach combines central expertise with distributed ownership. AI Squads aligned to individual lines of business gather market intelligence, identify relevant use cases, and work with technology teams to develop and operationalise them. Ideas originate close to client and business requirements while benefiting from reusable central capabilities.
Satyajit has prioritised skills including prompt engineering, LLMOps, rapid prototyping, and agentic AI frameworks, encouraging teams to experiment with a clear connection to practical application. Team members are given ownership of products, client engagements, and innovation programmes, creating opportunities to develop the next generation of AI leaders.
Making AI Part of the Delivery Model
Satyajit’s impact is clearly seen in the extent to which AI is becoming embedded in Evalueserve’s core delivery model. GenAI accelerators, proprietary Data Agents, and cloud-native automation now support activities across the data engineering lifecycle, from design and development to testing and operations. Alongside these capabilities, domain-specific research bots and decision-support platforms are designed around usability and integration into existing workflows.
Scale has not meant uncontrolled adoption. Satyajit advocates clearly defined use cases, controlled expansion, governance, and continuous performance monitoring, combining the pace of emerging technology with the disciplines required for enterprise deployment. This balance between innovation and operationalisation sits at the heart of his leadership.
Satyajit’s achievement is that he has helped establish the organisational structures, products, skills, and delivery practices required to make AI sustainable. He has demonstrated the shift facing data and AI leaders from proving that AI works to building an organisation capable of making it work repeatedly, responsibly, and at scale.
