Innovation without measurable impact is just noise: Fulcrum Digital’s Rajesh Sinha

As enterprises worldwide rush to integrate artificial intelligence into their core operations, technology companies such as Fulcrum Digital is focusing on what its founder calls “AI with impact.” The US-headquartered digital engineering company, which has a strong innovation base in India, is helping clients move beyond pilots and proofs of concept to measurable business outcomes. In an interview with TechCircle, Rajesh Sinha, Chairman and Founder of Fulcrum Digital, discusses how autonomous agents are redefining enterprise AI, on moving beyond AI experimentation, why India is central to the company’s global strategy, and how responsible, explainable AI is emerging as a non-negotiable business imperative. Edited excerpts.

Enterprises are investing heavily in AI, but many struggle to turn pilots into performance. How are you helping enterprises move beyond AI experimentation to achieve measurable business impact?

At Fulcrum Digital, we believe innovation without impact is simply noise. Our focus is to help enterprises move beyond experimentation to achieve tangible outcomes—whether that’s revenue growth, cost reduction, faster time-to-market, or superior customer experience. We use our enterprise AI operating model and platforms to embed intelligence into workflows, not just add it on. By tying AI innovation to measurable KPIs, we build trust in intelligent systems and accelerate transformation. Our “crawl-walk-run” approach ensures that every AI initiative aligns with business priorities and scales sustainably. Data and intelligence together, I believe, are what make truly great companies.

How do autonomous-agent frameworks differ from traditional AI models, and what problems are they solving today?

Traditional AI models are task-specific, relying on human-defined steps and oversight. Autonomous-agent frameworks go further—they combine reasoning, context, and the ability to act within workflows. At Fulcrum Digital, we see this as a shift from automation to “intelligence amplification.” These frameworks are enabling adaptive decision-making, dynamic orchestration of cross-system workflows, and real-time insights from structured and unstructured data.
For example, with a manufacturing client, our agent-driven supply-chain optimisation system reduced cycle time and improved throughput by linking upstream data with downstream monitoring. Autonomous agents are proactive, contextual, and self-learning—designed to evolve continuously.

India has become a global hub for AI innovation. How is Fulcrum Digital leveraging its India ecosystem?

India offers deep engineering talent, cost efficiency, and a vibrant innovation ecosystem. Fulcrum Digital has anchored its global AI engineering and platform development here, allowing rapid prototyping and scalable experimentation. We collaborate with startups, research labs, and universities to advance work on large language models, multimodal intelligence, and agentic AI. India gives us the ability to innovate fast, test effectively, and deploy globally.

Across BFSI, healthcare, and manufacturing, etc. where are you seeing the strongest demand and ROI from AI?

Each sector is adopting AI differently, but with strong returns. For example, in BFSI, we see trends such as fraud detection, risk modelling, personalised customer journeys, and AI-driven underwriting. Clients are seeing 20–30% process-cycle reductions and improved customer response times.In healthcare, we are seeing an uptick in areas such as patient triage, digital front-door engagement, and population analytics—leading to faster diagnoses and lower readmission rates. In manufacturing, there’s a greater momentum in areas like predictive maintenance, supply-chain orchestration, and quality automation that are improving throughput and overall equipment effectiveness. The key is to link every AI initiative to clear business metrics—cost, yield, or customer satisfaction—otherwise it risks remaining academic.

How do you ensure its AI frameworks remain responsible and transparent?

Responsible AI is core to our philosophy. Every model we deploy includes decision traceability, audit logs, and human-in-the-loop mechanisms. We build ethics-by-design through bias assessment, fairness testing, and region-specific compliance. Equally important is change management. For AI to succeed, people must trust how the system works. Trust, in fact, is central to Fulcrum’s culture and key to sustainable innovation.

How do you view Generative AI’s role in enterprise transformation?

Generative AI is powerful—but only when applied pragmatically. We integrate generative capabilities when they solve real problems, such as generating context-aware insights, automating regulated content, or powering conversational agents. We don’t deploy it for novelty. Our rule is simple: Does it move the business needle? If not, it stays on the shelf. We believe in “pilot fast, measure fast, scale what works.” Pragmatic innovation with measurable value matters more than hype.

How is the CIO/CTO mandate evolving in the AI era?

The CIO or CTO is no longer just a technology custodian—they are becoming a value accelerator. The role is shifting from managing systems to orchestrating intelligent platforms, from cost control to value creation. They must now collaborate across business units and ecosystems, balancing innovation with governance. The mandate today is broader, bolder, and more strategic—focused on enabling safe, scalable AI transformation.

What’s next for Fulcrum Digital’s AI innovation ecosystem in India?

India will remain our global AI nerve centre. We are scaling our engineering and domain teams to build sector-specific AI platforms for manufacturing, healthcare, and financial services. We’re deepening partnerships with deep-tech firms and academia to co-create IP and drive breakthroughs in agentic and multimodal AI. We’re also investing heavily in continuous learning—so our teams embody the “crawl-walk-run” mindset and stay ahead in ethics, governance, and next-gen AI infrastructure. In essence, we’re doubling down on India to build, deploy, and scale the enterprise AI platforms of the next decade.