Sharad Sanghi & Anindya Das: The Minds Behind Neysa’s Enterprise-Grade AI Revolution
Meet Sharad Sanghi & Anindya Das, Neysa Founder, is not a story about chasing hype. It is a story about timing, depth, and lived understanding of infrastructure—built by two founders who had already seen scale, failure, and transformation from the inside.
Sharad Sanghi, widely known for building and scaling Netmagic into one of India’s most respected data center and cloud services companies, spent decades working at the intersection of enterprise technology, infrastructure reliability, and operational discipline. Anindya Das, with deep experience across enterprise systems, data platforms, and large-scale technology environments, shared a similar vantage point: modern businesses were rushing toward artificial intelligence without the foundations to sustain it.
Neysa was founded in the early 2020s in India, at a moment when AI adoption was accelerating faster than enterprise readiness. While global narratives focused on applications and models, Sanghi and Das focused on what sat underneath—AI infrastructure, data systems, and enterprise-grade platforms that could make intelligence usable, reliable, and scalable.
The “why” behind Neysa was rooted in frustration. Enterprises wanted AI outcomes but were constrained by fragmented data infrastructure, cloud inefficiencies, and a lack of purpose-built platforms. The “how” was shaped by decades of operational experience: build a deeply engineered AI infrastructure platform designed for real-world enterprise complexity, not demos.
This is not a flashy founder story. It is quieter, heavier, and more deliberate. It is about two founders choosing depth over noise, systems over shortcuts, and long-term value over speed. What follows is the full journey—backgrounds, struggles, self-doubt, validation, leadership evolution, and the future vision that still keeps them awake at night.
1. Background and Early Life
1.1 Sharad Sanghi: Learning Infrastructure Before It Was Fashionable
Sharad Sanghi’s early life and education shaped his worldview around systems rather than products. Long before “cloud” became a default term, Sanghi was immersed in the realities of enterprise IT—uptime, reliability, security, and scale.
His formative years were defined by curiosity around how large systems stay functional under pressure. Education provided technical grounding, but it was real-world exposure that taught him what textbooks could not: infrastructure is invisible when it works and brutally visible when it fails. This belief would later define every company he touched.
1.2 Anindya Das: Depth Inside Complex Technology Environments
Anindya Das’s early career followed a parallel path. Rather than chasing consumer-facing glamour, he worked deep inside enterprise technology stacks, data platforms, and large organizational systems.
His exposure to how enterprises adopt technology—slowly, cautiously, and often painfully—gave him a grounded understanding of what innovation actually requires to survive inside real businesses. Both founders developed something rare: patience for complexity.
2. Founder and Company Overview
2.1 Who Are the Founders of Neysa
Meet Sharad Sanghi & Anindya Das, Neysa Founder, represents a partnership built on complementary strengths. Sanghi brought decades of infrastructure-building experience. Das brought enterprise technology depth and execution rigor. Neither came from a hype-driven startup background. Both came from environments where failure had consequences and systems had to work every day.
2.2 What Neysa Is Building
Neysa is an Indian AI startup focused on artificial intelligence infrastructure and enterprise AI platforms. Rather than building surface-level applications, Neysa operates in the deeper layers of the AI stack. The company works on AI infrastructure, data infrastructure platforms, and enterprise AI solutions that help organizations deploy, manage, and scale artificial intelligence reliably.
2.3 Market Served and Business Stage
Neysa serves large enterprises, data-heavy organizations, and businesses looking to operationalize AI rather than experiment with it. The company operates in the deep tech startup India ecosystem, targeting long-term enterprise adoption rather than rapid consumer scale.
3. The Problem, Insight, and Trigger
3.1 The Core Problem Enterprises Faced
The AI boom created a paradox. Enterprises wanted AI-driven outcomes but lacked the infrastructure to support them. Data was fragmented. Cloud costs were unpredictable. AI models struggled to move from pilot to production. This gap was not visible to outsiders, but it was painfully obvious to insiders like Sanghi and Das.
3.2 Personal Insight Behind Neysa
Both Sharad Sanghi and Anindya Das had witnessed the rise and fall of multiple technology waves. Over time, they noticed a recurring pattern: whenever new technologies hit enterprises, failure almost always started at the infrastructure layer. AI, they realized, was following the same trajectory. Without purpose-built platforms to support it, companies risked wasted investments, stalled initiatives, and eroding trust in the very technologies they hoped would transform their business.
3.3 The Trigger to Start Neysa
The trigger was not a single moment. It was an accumulation of conversations with CIOs, CTOs, and technology leaders who were overwhelmed. That accumulation turned into conviction: someone had to build AI infrastructure for reality, not for slides.
4. Early Days and Initial Struggles
The early days of Neysa were defined by clarity and uncertainty existing side by side. The founders knew the problem deeply. What they did not know was how quickly the market would mature. Building deep infrastructure is slow. Explaining it is harder. Selling it requires patience. Early assumptions around enterprise readiness were tested immediately. Many companies wanted AI but were not prepared to invest in foundations.
5. Failures, Setbacks, and Self Doubt
There were moments when progress felt invisible. Enterprise sales cycles stretched endlessly. Technical conversations took months to convert into action. Product decisions carried high stakes because mistakes were expensive. Self-doubt crept in quietly—not about the problem, but about timing. Was the market ready, or were they too early again?
6. Validation and Early Traction
Validation didn’t come in flashy headlines or media attention—it arrived quietly, in repeated conversations. Early enterprise customers started returning, not with simple requests, but with deeper, more complex challenges. That shift mattered—it was a signal of trust. Slowly but steadily, revenue traction followed, reinforcing the founders’ conviction that an infrastructure-first approach to AI wasn’t just a theory—it had a real, growing market.
7. Funding, Money, and Growth Constraints
Neysa’s journey reflects disciplined capital thinking. Funding was approached as a tool, not a trophy. Capital constraints forced focus. Every hire mattered. Every feature had to justify itself. Growth was intentionally controlled, prioritizing reliability over speed.
8. Team Building and Leadership Evolution
8.1 Early Hiring Challenges
Hiring for deep tech is unforgiving. The right skills are rare, and alignment with the company’s vision is critical. For Neysa, early hiring missteps weren’t measured in financial loss—they were felt culturally. Each mismatch had the power to slow momentum, unsettle teams, and test the founders’ patience and judgment.
8.2 Leadership Lessons Over Time
Leadership evolved from hands-on execution to system-level thinking. Delegation was learned slowly, sometimes painfully. Both founders embraced a shared philosophy: strong systems outlast strong individuals.
9. Growth, Scaling, and Operational Challenges
Scaling an AI infrastructure company is fundamentally different from scaling an app. Operational complexity increased with every deployment. Reliability became a daily obsession. Mistakes were treated as signals, not failures.
10. Personal Sacrifices and Burnout
The emotional cost was real. Long cycles, constant responsibility, and invisible wins created mental fatigue. Personal time blurred into work time. Burnout did not explode. It accumulated. Awareness became the first step toward sustainability.
11. Lessons, Beliefs, and Values
Over time, beliefs hardened into values. Depth over speed. Reliability over optics. Long-term trust over short-term growth. Both founders learned that enterprise trust is earned slowly and lost instantly. These values became non-negotiable.
12. Present Challenges and Future Vision
Meet Sharad Sanghi & Anindya Das, Neysa Founder, today operate in a rapidly evolving AI landscape. Competition is global. Technology shifts fast. Expectations rise constantly. Yet the obsession remains unchanged: building AI infrastructure that works in the real world. The future vision is not about being the loudest Indian AI startup. It is about becoming the most dependable. In a world chasing intelligence, Neysa is building the ground it stands on.
The FoundLanes View
At foundlanes, Culture Circle’s journey stands out not just for its headline-grabbing numbers but for what it reveals about building modern Indian startups—where trust, verification, and transparency can drive rapid adoption, even as losses widen. The Culture Circle 10x revenue growth reflects a clear market insight executed at speed, alongside the inevitable pressure of scaling through heavy spending on technology, hiring, and marketing. Stories like this matter because they show entrepreneurship as it truly unfolds: fast, demanding, and full of trade-offs, where short-term financial strain is often the price paid for long-term relevance and scale.