This Entrepreneur Raised Over $90 Million To Automate Document-Intensive Workflows, Reduce Manual Work, And Increase Efficiency

For Andrew Antos, the path to building a successful AI company began in an unlikely place: a family of scientists in the post-communist Czech Republic, followed by a brief career in law, and eventually a leap into the startup ecosystem at Harvard and MIT.

Today, Andrew is the founder of Klarity, an enterprise AI company that helps large organizations transform their operations with artificial intelligence, helping them achieve agility.

Klarity has raised over $91M and works with major enterprises to redesign processes, automate work, and drive measurable business impact through AI.

But the road to that point involved navigating early skepticism around AI, multiple pivots, fundraising challenges, and the constant pressure of building a company in a rapidly evolving technological landscape.

This is the story of how Andrew went from growing up in a competitive academic household in the Czech Republic to building a venture-backed AI company in Silicon Valley.

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

Growing Up in a Highly Competitive Scientific Family

Andrew was born in the Czech Republic just one year before the fall of communism. His childhood unfolded during a unique historical transition as the country shifted from a centralized socialist system to a capitalist economy.

Andrew’s upbringing was deeply shaped by a family steeped in science. For four generations, most members of his family had been scientists. His mother was a mathematician, his grandfather a chemist, and several relatives had made important scientific contributions.

Growing up in that environment created an intense academic culture; excellence was not optional. It was super intense and super competitive. Andrew recalls how deeply performance was ingrained in his household. Getting anything less than the best results was seen as unacceptable.

Even an A grade could be questioned. If he proudly shared that he received an A in school, Andrew’s mother might respond: “So you’re resting on your laurels?” That constant push toward excellence shaped his mindset early.

The 1990s in the Czech Republic were also an exciting time economically. Capitalism was rapidly taking hold, creating an atmosphere in which ambition and opportunity suddenly became visible. For Andrew, that environment fostered a deep curiosity about business, innovation, and technology.

The Unexpected Detour Into Law

Despite his strong technical interests, Andrew made a surprising decision at the end of high school.He decided to become a lawyer; his reasoning was pragmatic. He already understood technology well, having taught himself basic programming during high school.

Andrew believed that combining technological knowledge with legal expertise would provide a valuable advantage, especially since most lawyers struggled with technical topics. During his undergraduate years, he focused heavily on technology-related legal topics.

Eventually, Andrew joined a U.S.-based law firm, where he worked on technology M&A, regulatory matters, and corporate structuring. But it did not take long for him to realize that law was not his long-term path.

Within about a year, Andrew had a clear realization. He didn’t want to be a lawyer. The core problem was the nature of the work itself. Law felt fundamentally uncreative. Most of the time, it involved reviewing precedents, replicating existing structures, and selling time rather than creating new value.

Entrepreneurship and Building Something Unique

For Andrew, that was deeply unsatisfying. Entrepreneurship, by contrast, offered the possibility of building something original.

Still, the legal experience was not wasted. Working in technology M&A gave him valuable insight into corporate structures, equity issuance and grants, venture investments, and deal negotiations. Being part of a hyper-growth company and leading it helped him understand and anticipate problems.

That knowledge would later give Andrew an advantage as a founder navigating fundraising and company building. He learned how a corporation works and how success hinges on finding a really strong product-market fit.

Yet the most valuable skill he gained during those years was something simpler: communication. Law taught him how to write clearly and persuasively, especially in emails and written arguments. He trained to be succinct and to articulate value well.

Ironically, that skill became extremely valuable when Andrew later had to cold-email potential customers and investors during the early days of his startup.

The Harvard Move That Changed Everything

After realizing he wanted to pursue entrepreneurship, Andrew needed space to think. Working 100-hour weeks at a law firm left little room for creative exploration.

So he decided to pursue a master’s degree at Harvard, which gave him both the intellectual environment and the time to explore startup ideas.

There was also a deeper motivation behind his move to the United States. His family history played a role. Some of his relatives had created important inventions during the communist era, but were unable to benefit financially because intellectual property rights were not protected.

One example stood out. One of his great-aunts co-invented soft contact lenses, yet she received only a plaque of recognition and never saw financial returns. Andrew wanted to build companies within a system that rewarded innovation and offered stability, longevity, and a large market.

For him, that meant the United States.

Meeting His Co-Founder at MIT

Shortly after arriving at Harvard, Andrew cross-registered for a startup class at MIT called New Enterprises (15.390). It was only his third week in the U.S. when something pivotal happened. In that class, he met Nischal Nadhamuni, a computer science student at MIT.

Nischal had just finished his undergraduate degree in computer science at MIT, specializing in machine learning and natural language processing. The two immediately clicked. They decided to team up for the class project, which soon evolved into something much bigger.

After spending hours walking around Cambridge discussing ideas, the duo reached a conclusion. They should start a company together. Even more interestingly, they decided to start an AI company in September 2016. At the time, artificial intelligence was not yet the global phenomenon it is today.

But inside MIT, something was clearly happening. Machine learning classes were so popular that students slept overnight outside professors’ offices just to secure seats. To Andrew and his future co-founder, it felt obvious. AI was going to be huge.

Starting an AI Company Before the AI Boom

Andrew and Nischal initially focused on automating legal work using artificial intelligence. Their idea was to apply AI to legal processes such as due diligence, document analysis, and contract review. They began building the concept as a class project.

After graduating, the duo officially launched the company in 2017. But when they introduced the idea to the real world, they ran into a major problem. Nobody cared. Artificial intelligence simply was not a mainstream topic yet. Even worse, the technology itself was not mature enough.

This was years before large language models and modern generative AI tools. Andrew concedes that the systems available at the time were clunky, expensive, and difficult to deploy. Despite those challenges, the company managed to survive.

Andrew and Nischal joined Y Combinator, which helped them gain early traction and build a network. Instead of pursuing one unified product, they solved many individual problems for customers. The result was a business that looked more like AI consulting than a product company.

But it kept the nascent company alive. And survival turned out to be one of their most important advantages.

Finding Product-Market Fit

After several years of experimentation, the breakthrough finally came in 2020. Andrew and Nischal discovered a powerful use case in enterprise accounting teams.

Large companies like DoorDash employ teams of people whose job is to read documents, extract data, and reconcile information with ERP systems. These tasks are repetitive, time-consuming, and expensive.

Andrew and his team built AI systems that could automate many of those processes. This became their first real product-market fit. With that traction, the company began scaling rapidly. They signed major enterprise customers and raised their Series A and B venture funding to accelerate growth.

From Product to Transformation Platform

As the company grew, Andrew noticed something surprising. Customers weren’t just buying software; they were asking for full-scale AI transformation projects.

Each project they were hired to do involved several steps, starting with mapping the company’s current process and understanding how it worked. Next, they would redesign the process for automation and implement AI solutions. They’d also train employees to work with AI.

Ironically, the most painful part of their business was the implementation phase. So the team began building internal tools and AI agents to simplify the process. Eventually, Andrew showed those tools to customers. The response was immediate—customers wanted to buy them.

What started as internal tooling became a new product, which eventually grew even faster than the original business—quickly becoming its core driver.

The Business Model Behind Klarity

Klarity operates on a subscription-based enterprise model. Instead of charging per task or transaction, the company structures subscriptions around organizational transformation. The process usually begins by defining the scope.

For example, a company might want to transform its finance operations, HR processes, sales operations, revenue operations, or commercial operations to scale faster and compress revenue cycles.

Once the scope is defined, Klarity provides an enterprise subscription that allows organizations to use the platform across teams. This approach focuses less on individual tools and more on enabling large-scale organizational change through AI.

As Andrew points out, they started Klarity about 8 years ago, even before ChatGPT, Anthropic, or similar companies, as we know them today, launched.

Surviving Being Too Early

One of the hardest challenges Andrew faced was being too early. As he reflects, it created complexities and challenges because adoption was harder to achieve. However, Andrew and Nischal successfully navigated the challenges in the early years so they could wait for the wave to form, as it has now.

Klarity launched even before the famous “Attention Is All You Need” paper introduced the transformer architecture, which later powered modern AI models. For years, the market simply wasn’t ready.

Yet Andrew believes their survival during that period ultimately became a competitive advantage. His philosophy was simple: “Stay alive.” As he once read in a quote that stuck with him: “Every day your company survives, your chances of success grow exponentially.”

As Andrew underscores, every company needs to constantly obsess about finding customers. Klarity’s always had customers, which meant that they learned how to sell products, support customers, and drive real value. Companies that survive long enough eventually find themselves in the right moment.

In the initial few years, Klarity operated more as a consulting business than a product business. It was solving various kinds of use cases. Markets evolved, technology advanced, and customer preferences shifted. When the AI boom arrived, Klarity was ready. When the market caught up, it simply executed.

Andrew and his team could build a product that the world’s largest companies can rely on and trust.

Raising Over $91M: The Reality of Startup Fundraising

Klarity has raised $91M+ in venture funding, but the fundraising journey was anything but linear.

Andrew and Nishcal went through the accelerator program and raised money from top, high-profile investors, a process that was challenging for foreigners, as was building networks and being intentional about it.

But Andrew observed an interesting pattern—fundraising tends to alternate between easy and difficult rounds. The first small round of “ramen money” came together in three days. Next, they had to move the company from Boston to Silicon Valley, and getting into Y Combinator required three attempts.

The $2M seed round raised in 2018 closed in 24 hours, because Andrew secured several big customers, including ServiceNow. However, the Series A round was extremely difficult because no one cared about AI in 2021.

Surprisingly enough, the Series B round closed in three days. For Andrew, three lessons stood out from this experience. Firstly, you need strong traction and great numbers. Secondly, you need a clear story that explains the problem you’re solving and why the solution is unique.

Thirdly, timing is random, and investor interest is often influenced by market trends and internal investment theses. Sometimes you are building exactly what investors want. Other times, you are too early.

Storytelling is everything that Andrew 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 Peter Thiel, Silicon Valley legend (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 a Network as a Foreigner

Andrew also had to build his network from scratch as an immigrant founder. Y Combinator played an important role in helping him meet early investors and mentors. But he also discovered something powerful about Silicon Valley and San Francisco. The ecosystem is highly meritocratic.

People tend to evaluate founders based on whether they’re building something interesting, getting traction, and securing enterprise customers. For Andrew, that openness made Silicon Valley uniquely attractive compared to many other ecosystems.

The Vision: Helping Enterprises Become Exponential Organizations

Today, Klarity focuses on helping large companies implement AI in a way that actually changes business outcomes by helping enterprises adapt continuously.

Klarity consistently observes how work gets done across an enterprise to continuously make recommendations, enabling compounding change.

As Andrew points out, the problem statement that every single executive in a large company, like a Fortune 500 company, is grappling with today is how to implement AI to meaningfully improve their operating or financial metrics.

Their focus is on driving revenue quickly, lowering costs, and accelerating the business. Andrew calls this the “80/20 problem.” Buying an AI license might represent only 20% of the challenge. Companies can purchase a GPT, Cloud, or Gemini license or any other AI tools.

The real challenge is changing the management around it and training employees to use the tools so they are faster, better, and work more efficiently—the remaining 80%. He emphasizes that getting value from AI means aligning both people and processes with automation.

Ultimately, it’s about redesigning processes, changing people’s roles and responsibilities, and supporting them through “the roll-ups,” as Andrew puts it.

Klarity addresses complexities and challenges through a combination of software and AI agents that help companies rethink how work gets done. The result can be dramatic. A full-stack account executive can handle tasks without needing a business development representative.

In one example, a customer reduced a process that previously took 60 days down to just 3 days. This kind of transformation allows companies to operate faster, more efficiently, and with fewer constraints.

Andrew envisions a world where Klarity can help customers build exponential organizations where people are happier to work. This means they’re more productive, move faster, and get more satisfaction from their work.

Advice to His Younger Self

Looking back on his journey, Andrew would give himself two key pieces of advice.

1. Simplify Everything: The best startup ideas are simple and easy to explain. Founders often overcomplicate their products and messaging.
2. Invest in Relationships Early: Every year, Andrew says he realizes something surprising. Relationships matter even more than he previously believed, and strong networks open doors.

Final Thoughts

Andrew Antos’ journey highlights an important truth about entrepreneurship. Success often comes not from perfect timing, but from persistence through imperfect timing. He started an AI company years before the market was ready.

Instead of quitting, Andrew kept the company alive long enough for the world to catch up. When the AI wave finally arrived, Klarity was already positioned to ride it. And that preparation turned early struggle into a lasting advantage.

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

• Growing up in a highly competitive family of scientists in the post-communist Czech Republic instilled in Andrew Antos an early obsession with excellence, curiosity, and intellectual rigor.
• His brief career as a technology lawyer exposed him to M&A, venture capital structures, and corporate strategy—knowledge that later proved invaluable in building and fundraising for his startup.
• A pivotal moment came when Andrew met his co-founder, Nischal Nadhamuni, at MIT, where their shared belief that AI would become transformative led them to launch Klarity in 2017.
• In the early years, Klarity survived by operating more like an AI consulting company, solving custom problems for customers while waiting for the technology and market to mature.
• True product-market fit emerged in 2020 when the team discovered a powerful use case automating repetitive accounting and document-processing workflows for large enterprise teams.
• Klarity’s fundraising journey—raising over $91M—demonstrated how venture capital cycles often fluctuate between effortless and extremely difficult rounds depending on traction and market timing.
• Andrew’s biggest entrepreneurial lesson is simple: survival matters—because every additional day a startup stays alive increases the probability that it will eventually meet the right market moment.

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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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