Founder Spotlight:Mariya George, Cleareye.ai

In a relatively short space of time, AI has moved from a boardroom buzzword to become a necessity across a range of sectors. This has led to a proliferation of innovative businesses offering novel, agile solutions.

One such organisation is Cleareye.ai. Since its founding in 2019, the company has carved out a niche in the complex world of trade finance by applying advanced AI to solve the persistent, costly, and time-consuming burdens of document processing and compliance.

Deepesh Patel, Editor at Trade Treasury Payments (TTP), sat down with Mariya George, co-founder and CEO of Cleareye.ai, in the TTP Studios in London to discuss the challenges – both technical and otherwise – of deploying AI in banking, along with her experiences of leadership, and the future of trade finance in the AI age.

Building foundations

George’s career was built around a deep engagement with banking technology long before establishing Cleareye.ai. After finishing college in India, she joined the tech firm UST. “My job earlier on in my career,” she explains, “was to understand what the banking customer’s needs are and, as a tech company, how to help them with their tech needs”.

Over the next decade, she rose through the ranks at UST, eventually leading the firm’s banking portfolio. By managing relationships with major industry institutions like Morgan Stanley and State Street Bank, she gained invaluable insights into their challenges and ways of doing business.

The first pivot towards AI occurred around 2012. As George recalls, “This was when AI was a buzzword. Everybody was talking about AI, trying to figure out what AI meant”. In collaboration with Stanford AI Labs, she led an effort to commercialise AI for workflow automation. This would prove to be a pivotal experience, not only due to the project’s technical success, but also because of the personal realisation she had that she wished to start a company of her own.

“I come from a business family,” she explains. “I was the first in my generation to really go for a job outside business,” so starting a business seemed somewhat natural. With the inspiration to show her children that hard work, perseverance, and consistency yield results, she founded Cleareye.ai. While she freely admits the decision was “scary”, it was supported by a strong family foundation and a clear vision: building an enterprise-ready AI platform.

The pandemic, resilience, and scaling for success

The early years of Cleareye.ai were always going to be defined by challenges with such lofty ambition, but the growing pains were exacerbated by unforeseen circumstances. Just one year after the business’ inception, the COVID-19 pandemic hit and changed the way the world operated. This meant significant uncertainty for a young company already tackling the daunting undertaking of trying to penetrate a notably risk-averse banking sector.

“How do you sell to someone when you cannot meet anybody or even talk to them?” George reflects. Ultimately, though, the pandemic period became a time of focus. Without the distractions of ‘normal’ operations, the team could dedicate themselves to engineering, ensuring the platform they were developing could be enterprise-ready when the market (and the world) reopened.

“The turning point for the company,” George explains, “was J.P. Morgan.” In 2022, just three years into Cleareye.ai’s existence, J.P. Morgan was onboarded as a customer, eventually becoming an investor also. From this turning point, Cleareye.ai now boasts a team of 140 people worldwide, continuing to address the complex hurdles banks face.

Leadership in a male-dominated landscape

Even with Cleareye.ai being unquestionably a success story, George acknowledges the inherent challenges she faced as a female CEO in the technology sector. “It is definitely more challenging to be a woman founder, co-founder, and CEO, which is a fact,” she explains. Recognising and facing these challenges, George advocates for a balanced approach to leadership. While early-stage hurdles require significant grit and courage, she emphasises that once a firm is established, the focus shifts to delivering precision, quality, and confidence to customers.

Reflecting on her own growth as a leader, George shares how she learned to separate personal emotion from the realities of running a business. “Problems are mine to solve,” she notes, adding, “There’s no point in sharing with anyone else… we’ll work as a team to solve it, but they don’t need to see how I feel about it”. This disciplined approach, maintaining personal investment while regulating the emotional element, has been essential for building a scalable and sustainable company in her view.

AI’s evolving role in trade finance

In recent years, there have been fundamental shifts in how banks approach AI. 2020 to 2023, for instance, was characterised by what the tech industry refers to as “sandboxing” – i.e., testing AI in isolated environments to figure out how and where to use it. Today, the landscape is increasingly dictated by board-level mandates for wider AI adoption with explainability and model risk governance as accepted “table stakes”, as George describes it.

George emphasises that the key differentiator within the sector today is “domain-based AI”. She argues that general-purpose Large Language Models (LLMs) often fail when applied directly to trade finance because they lack the necessary context for the huge amounts of unstructured data they’re dealing with. “You cannot use general purpose LLMs to solve a trade finance problem,” she explains.

The future of AI, in her eyes, lies in reasoning – a move beyond mere automation to intelligent decision making that supports and augments the “human doing the work to do it smarter”.

The possibility of truly autonomous trade?

Looking ever forward, George believes the industry is on the verge of significant transformation, with paper-based processes finally giving way to true digitalisation. Autonomous AI agents are currently limited in their use by regulatory caution, but as George notes, the architectural groundwork is being laid. “I don’t think we are there yet,” with regard to agents, she explains, but confidently states that “when it’s there, we’ll be ready”.

With a short but already well-established legacy of consistent execution and commitment to solving domain-specific challenges, George and Cleareye.ai are positioning themselves as catalysts for the next generation of global trade.

The ultimate potential is to bridge the multi-trillion-dollar trade finance gap with AI technology. By making trade transactions faster, more efficient, and more reliable, she is optimistic that banks will be able to process transactions that are currently excluded due to high burdens. “I’m hoping that products like ClearTrade eventually will be able to help banks do that and bring down the trade deficit,” she concludes.

Prefer to listen? The full conversation is also available as a podcast below.