He Raised $60 Million To Build An AI Platform Helping Organizations Gain Visibility And Control Over Their Enterprise-Wide Data Processing

Abhi Sharma’s entrepreneurial story begins in the Himalayan foothills and winds through Silicon Valley. His narrative traces venture-backed startups, billion-dollar exits, and now, a mission to reshape how we govern AI and data in a rapidly evolving digital world.

A second-time founder and a technologist at heart, Abhi has built and sold companies, raised over $60M in venture funding for Relyance AI, a category-defining platform at the intersection of data security, AI governance, and privacy compliance.

Appearing on the Dealmakers Podcast, Abhi talks about the lessons he learned when building a business during the pandemic and choosing not to hire an internal recruiting team.

Listen to the full podcast episode and review the transcript here.

Humble Beginnings and the Spark of Curiosity

Born in northern India, Abhi grew up in a lower-middle-class academic household, rich in values but modest in resources. Despite financial limitations, he developed a love for math and science early on.

Abhi first dreamed of becoming a doctor until an uncle challenged him to dissect a frog. That moment quickly redirected his interest from medicine to machines.

“I realized I liked the idea of being a doctor more than the reality of it,” Abhi recalls with a laugh. “But once I touched a computer, I was hooked. I could build something and share it with the world.”

Abhi got keenly interested in computers because he could build things and write some early apps. He was fascinated by computers and got his first system at the end of his school career. He loved using the dial-up connection to connect to the world.

Keen Interest in Building Things that Have an Impact

That desire to build and see his work’s direct impact drove Abhi away from prestigious corporate offers and into the nascent startup ecosystem in India. At that time, “joining a startup” was far from the norm, especially for someone with a top-tier computer science background.

Back then, the status quo for kids completing their undergraduate studies with great scores was to get into Microsoft, Google, or IBM, since they could earn well. Abhi wanted not only to build something but also to have customers give him direct feedback. That was important for him.

Thus, Abhi leaned into the unknown. His early bet paid off when he was sent to the U.S. to help open new markets. He performed really well at the platform and enjoyed his customer-facing role.

After working for a while in Los Angeles, Abhi pursued graduate studies in machine learning at Carnegie Mellon University.

While at the university, he had the opportunity to read a paper that outlined how the most powerful technologies seem to blend into day-to-day life without people noticing them. Abhi remembers being captivated and inspired by this concept.

He loved the idea of craftsmanship and that creators don’t need to be pompous about their technology because it just works. It simply means it is done well. At CMU, Abhi learned from some of the best professors in machine learning at the time.

Lessons from a Rocket Ship: AppDynamics

After CMU, Abhi joined AppDynamics, a hyper-growth startup Cisco later acquired for $3.7B, an incredible outcome. Here, he forged a close bond with Jyoti Bansal, the company’s founder and long-time mentor. Abhi recalls quickly learning a lot. Eventually, Jyoti Bansal joined the board of Relyance AI.

At AppDynamics, every person’s contribution mattered in scaling the company. Abhi was also impressed by how intentionally Jyoti worked to craft the culture. He absorbed the principles of ownership and agility, which they called “startup within a startup.”

Everyone was supposed to move with a lot of agency, a cultural element that has remained with Abhi. “AppDynamics was my masterclass in scaling culture, obsessing over customer pain points, and building tech that mattered from scratch,” he says.

Abhi worked on the early observability stack, which is still the core perspective on how Relyance builds its technology and infrastructure today. He credits working at AppDynamics with being activated into entrepreneurship and diving into the unknown.

Going Solo: The Birth and Exit of FogHorn Systems

Eager to build something of his own, Abhi co-founded FogHorn Systems, an IoT analytics startup that predated and paralleled today’s unicorn Samsara. The company emerged from a Palo Alto incubator and was sold to Johnson Controls in 2019.

Abhi remembers connecting with a few technical engineering minds, and together, they joined an incubator to build a company. The incubator intentionally funded specific categories or styles of startups, and Abhi fit the bill.

They ran the company for five years before the acquisition. Building, scaling, and selling FogHorn gave Abhi the exciting experience of the full cycle of entrepreneurship and reaching the finish line. It gave him visibility and clarity.

While the exit was a milestone, it was also a wake-up call. “I didn’t fully own my founder role,” Abhi reflects. “I let fear get in the way.”

Abhi learned the hard way that if you’re going to build something special, you need to believe that you are the right person to lead it—naivety and all.

Reinventing with Intention: The Genesis of Relyance AI

After FogHorn Systems’s acquisition, Abhi did some soul-searching. His next move had to be intentional. He wanted to operate at the intersection of three deep technical interests: compilers, machine learning, and observability.

Abhi started exploring areas where he could deploy these interests and have a meaningful impact on the world. He had two areas in mind–real-time biotech and data governance. He chose data governance because of his experience and proximity to the machine learning community.

All signs pointed toward a significant global gap: data protection and security in the age of AI. Abhi was confident he had something between observability and machine learning that could be uniquely applied in this space with an entirely different perspective on solving these problems.

As a business person, he took a pragmatic perspective and created a checklist. Topping the list was the question, “How fast can I build at least a $500M ARR business and work backwards from there?”

This question formed Abhi’s hypothesis for Relyance AI. Today, the company sells software as a service (SaaS) on an annual subscription model.

A New Category: Convergence of Privacy, Security, and AI Governance

The company sells a modular SaaS platform that provides tools for privacy compliance, security posture management, and AI governance. This platform allows customers to mix and match capabilities based on scale and need.

Today, Relyance AI has over 120 employees and has raised $60M in funding, despite launching and fundraising at the height of the pandemic. Talking about his funding experience, Abhi revealed that raising the seed round wasn’t very challenging.

Since he is a second-time founder, he has more credibility and a great network of people. Investors could see the unique strategy they were using to approach the problem. Seed rounds are always about the firm’s founder more than the idea.

Storytelling is everything that Abhi Sharma was able to master. The key is capturing the essence of what you are doing in 15 to 20 slides. For a winning deck, take a look at the pitch deck template created by Silicon Valley legend, Peter Thiel (see it here), where the most critical slides are highlighted.

Remember to unlock the pitch deck template that founders worldwide are using to raise millions below.

Building the Right Culture: The Recruiting Lesson

One of Abhi’s most significant takeaways from the early Relyance journey was the importance of building an internal engine of recruiting culture.

Abhi recalls, “Initially, hiring came easily. My old team from FogHorn Systems, including folks from MIT, Stanford, and Google, followed me. It was a huge moment of pride. But I didn’t intentionally craft a recruiting engine. And that delayed our ability to scale.”

They ended up hiring people for the executive team and other key early employees, some from third-party agencies, who were not a good fit for the company. Eventually, they built an internal talent engine rooted in cultural fit, intentional processes, and proactive sourcing.

But the delay, Abhi admits, cost them valuable time in the early scaling phase. It’s not just about finding the right talent; it’s about building an engineer with a culture and a point of view that can start to attract the right talent to the company.

The Vision for the Future

Abhi sees a world split in two–before AI and after AI. In his mind, Relyance AI is the infrastructure highway that organizations will use to govern, trust, and deploy AI responsibly.

“Data quality, trust, security–all of it now directly impacts business outcomes. Our mission is to be the backbone that ensures your AI behaves the way it’s supposed to,” Abhi says. He notes three primary things that are fundamentally changing the world of software.

First, data used to be an inert side effect of code and API. Now, data quality, distribution, amount, and frequency completely determine business outcomes. The quality of an AI output is highly correlated with the input given to it.

Thus, some people who are good at prompts get a better answer than some people who aren’t good at prompts. This is why people spend a lot of time crafting the correct prompt.

Second, software is no longer a tool that you program; it now has agency because AI agents will exhibit non-deterministic behaviors.

When you combine these aspects, like observability, trust, and visibility in your data, accountability becomes foundational for compliance and security, and for customers to get the business outcome they want. AI is now the underlying factor.

Earlier, organizations had siloed perspectives on DLP, data security posture management, compliance, DSPM, GRC, data governance, and data catalog. But now, all of these things are converging into a singularity.

If you look at the jobs to be done and the problems people are trying to solve, 95% are the same. Relyance AI is a counterintuitive native AI approach and a platform built to address these problems.

Abhi realized that Relyance AI would not be in the best position to serve customers without a strong technological foundation. Since data now drives software behavior, he wanted to be able to solve the most complex and correlated problems.

Data, its quality, protection, frequency, and distribution will directly determine business outcomes. Relyance AI is here to help our customers trust, protect, and govern it so that they can run their business while the platform handles all the other aspects.

Advice to Founders

Abhi’s advice to his younger self—and to any founder starting out:

• Build everything with high degrees of intention, from recruiting to culture to product to your technology architecture to your ICP. Whatever you don’t design with intention will be ugly by default. You might get lucky, but not always.
• Be a relentless, truth-seeking machine for product-market fit, and reinvent yourself at every stage. Get exceptionally good at this step.

His final reflection? “I’d still do it all over again. Entrepreneurship gives me joy. But if I can avoid a few landmines the second time, even better.”

Listen to the full podcast episode to know more, including:

• Yield to your inner founder spark. Even with uncertainty, embracing leadership is essential to shaping the company’s direction and culture.
• Relying solely on personal networks can stall growth. Abhi learned that a structured, values-driven recruiting system is critical for sustainable team scaling.
• Relyance AI was built on the conviction that privacy, security, and AI governance would converge—a bet that’s now paying off as these domains rapidly intersect.
• Rather than follow conventional startup advice to narrow focus, Relyance AI was built as a platform from day one, anticipating the merging of compliance, data security, and AI governance.
• In an AI-first world, data quality, frequency, and protection are directly tied to business outcomes, making governance and observability mission-critical.
• The pandemic transformed pitch delivery almost overnight. Abhi’s experience shows that adaptability and a strong co-founder dynamic matter more than ideal timing.
• Abhi emphasizes that being a founder means constantly evolving—becoming a product-market fit machine and mastering new aspects of the business at every stage.

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Keep in mind that storytelling is everything in fundraising. In this regard, for a winning pitch deck to help you, take a look at the template created by Peter Thiel, the Silicon Valley legend (see it here), which I recently covered. Thiel was the first angel investor in Facebook with a $500K check that turned into more than $1 billion in cash. 

Remember to unlock for free the pitch deck template that founders worldwide are using to raise millions below.

 

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