Christian Nentwich, the visionary founder of the London-based data automation firm Duco, is returning to the CEO seat effective March 16, 2026. After a two-year stint as a board member, Nentwich is stepping back into the leadership role to guide the company through a period of explosive growth in artificial intelligence. Having previously led the company for nearly 14 years, his return marks a pivotal moment as the firm looks to integrate advanced AI capabilities while maintaining its commitment to no-code simplicity for financial institutions.
You are stepping back into the CEO role after serving as a board member for the last two years. How will your leadership approach differ from the previous administration, and what specific steps are you taking to ensure a seamless transition with the outgoing leadership team?
Returning to the helm feels like a natural evolution rather than a jarring shift, largely because I have remained very close to the company’s inner workings during my time on the board. My focus now is on leveraging the robust operational foundations that Michael Chin built, which I often describe as a much stronger “engine” than we had during my initial 14-year tenure. To ensure this transition is entirely seamless, Michael and I are speaking almost daily, coordinating every move to maintain the momentum he generated. He is staying on as a senior advisor to support the leadership team and preserve key customer relationships, allowing me to hit the ground running without losing any historical context or client trust.
The rapid evolution of AI model capabilities presents unique challenges for the financial services sector. How can no-code platforms help firms navigate strict regulatory requirements while adopting agentic AI, and what specific innovations are most critical for data reconciliation and ingestion today?
We have to take the current exponential explosion in model capabilities very seriously, especially when operating within the tight guardrails of regulated industries. Our no-code platform acts as a critical safety buffer, allowing finance and operations teams to manage, ingest, and validate structured and unstructured data without the risks inherent in complex, hard-coded systems. The most critical innovation we are pushing right now is the integration of intelligent document processing (IDP) to handle the massive influx of varied data types that modern firms face. By making these AI-driven tools accessible through a no-code interface, we empower our customers to safely adopt agentic AI operations while ensuring every piece of data remains fully auditable and compliant.
Re-engaging with nearly 200 employees and a portfolio of top-tier customers in a single week is an intensive undertaking. What metrics will you use to gauge the success of these initial conversations, and how will these insights shape your immediate product innovation roadmap?
In my first week back, I am personally reaching out to all of our almost 200 employees to realign our internal culture with the rapid pace of current technological shifts. I am also having direct conversations with our top customers to signal that our primary focus has sharpened on product innovation and helping them navigate the difficult AI journey. The success of these meetings won’t just be measured by sentiment, but by how quickly we can translate their specific friction points into our development sprints for the coming quarters. We want to hear exactly where the reconciliation process is slowing them down so we can deploy our AI technology to solve those high-pressure bottlenecks immediately.
With the recent integration of intelligent document processing and a focus on reaching profitability this year, how do you plan to balance organic growth with potential future acquisitions? What are the practical trade-offs of scaling operations without seeking additional external capital at this time?
We are in a very fortunate position where we do not need to raise additional capital, as we expect to achieve profitability within this calendar year. This financial discipline allows us to focus on organic growth and the deep integration of the Metamaze acquisition, which significantly bolstered our document processing capabilities. While the support of our majority shareholder, Nordic Capital, remains steadfast, we are prioritizing the optimization of our current “engine” to ensure we scale sustainably. The trade-off of forgoing external capital is that it forces a certain level of strategic rigor, ensuring that every innovation we pursue is directly tied to customer value and long-term stability.
What is your forecast for AI-driven data automation in the financial sector?
I anticipate that the financial sector is moving toward a reality where data automation is no longer a luxury but a fundamental requirement for survival. We will see a shift where agentic AI moves beyond simple task execution and begins to handle complex, multi-layered data validations across global markets with minimal human intervention. The focus will transition from simply “ingesting” data to “understanding” it contextually, which will drastically reduce the time spent on manual exceptions. Ultimately, the winners in this space will be the firms that can adopt these powerful models safely, using platforms like ours to bridge the gap between cutting-edge AI and the rigid demands of financial regulation.
