Priya Jaiswal stands at the forefront of the modern financial evolution, bringing a wealth of experience in market analysis and international portfolio management to the table. As fintech moves beyond simple digital interfaces toward autonomous intelligence, her insights provide a roadmap for how corporations handle their most vital asset: liquidity. With the recent news of Embat securing a significant Series B round to fuel its “agentic treasury” vision, Priya offers a deep dive into the technical and strategic shifts redefining the relationship between AI and the corporate CFO. This discussion explores the transition from manual accounting to real-time, autonomous financial optimization across the European landscape.
You recently secured €30 million in Series B funding, bringing your total capital to €50 million. How do you plan to allocate this new capital to sustain your current momentum, and what specific growth milestones must you reach to justify the continued backing of long-term investors?
Securing this €30 million injection is a pivotal moment that allows us to deepen our roots as an AI-native powerhouse while scaling our physical presence across Europe. We are funneling a massive portion of this capital into our product suite to ensure our technology remains the gold standard for the 400 corporate clients who already trust us with their financial operations. To keep investors like Cathay Innovation and Creandum confident, we must demonstrate that our total €50 million in funding translates into a dominant market share in the UK and Ireland. Our roadmap focuses on hitting aggressive user acquisition targets while proving that our “agentic” systems can handle increasingly complex cross-border transactions without friction. It is about moving from a high-growth startup to an indispensable piece of infrastructure for the modern enterprise.
Treasury management is shifting toward an “agentic” model where AI autonomously handles reconciliation and cash optimization in real time. What specific technical architecture is required to support this autonomy, and which manual tasks will your 400 corporate clients see disappear first as this technology matures?
The shift to an agentic model requires a sophisticated AI layer that sits directly on top of existing accounting systems and payment infrastructures, allowing for a seamless flow of data. Our goal is to move past simple reporting and into a reality where the system identifies a discrepancy and fixes it before a human even opens their laptop. For our 400 clients, the first things to vanish are the grueling hours spent on manual bank reconciliation and the constant, stressful checking of cash positions. We are building a system that breathes with the market, performing real-time optimization that used to take days of spreadsheets and phone calls. This autonomy transforms the treasury department from a cost center focused on data entry into a strategic hub focused on high-level decision-making.
The TellMe AI analyst operates directly across accounting systems and payment infrastructures. How does this tool bridge the gap between basic reporting and proactive financial hedging, and what specific metrics do you use to ensure the accuracy of these autonomous forecasting and optimization decisions?
TellMe acts as the cognitive engine of the platform, reaching into the deep architecture of a company’s financial history to predict future liquidity needs with startling precision. By integrating forecasting directly with hedging capabilities, the tool can suggest or execute protective measures against currency fluctuations or interest rate shifts before the volatility hits. We measure the success of these autonomous decisions through rigorous accuracy metrics, comparing AI-generated forecasts against actual cash flows to ensure a minimal margin of error. It is about creating a sense of total visibility, where the platform doesn’t just tell you what happened yesterday, but prepares your balance sheet for what is coming tomorrow. This proactive stance is what separates a modern treasury platform from a traditional, static ledger.
Expanding into the UK and Ireland requires a significant scale-up of local teams and go-to-market strategies. What unique regulatory or market-specific challenges have you encountered in these regions over the past year, and how will your leadership team adapt its approach to compete effectively?
Entering the UK and Ireland markets a year ago was a strategic test that required us to respect the unique regulatory nuances of the London financial hub and the Irish tech corridor. We have learned that these markets demand a high degree of localization, particularly in how we interface with local banking rails and navigate specific compliance frameworks. To compete, we are significantly scaling our local teams under experienced leadership to ensure our go-to-market strategy feels homegrown rather than imported. This isn’t just about hiring more people; it’s about infusing our operations with local expertise that can navigate the specific anxieties and ambitions of British and Irish finance directors. We are doubling down on our presence there because we believe the appetite for AI-driven efficiency in these regions is among the highest in the world.
What is your forecast for AI-powered treasury management?
I foresee a world where the “human-in-the-loop” becomes a strategic overseer rather than an operational worker, as treasury management becomes almost entirely self-correcting. Within the next few years, the manual reconciliation of payments will likely be viewed as a relic of the past, much like paper ledgers are today. We will see AI agents negotiating better rates with banks and automatically moving liquidity across borders to capture the best yields in real time. This evolution will lower the barrier for mid-sized companies to access sophisticated financial strategies that were previously only available to global conglomerates. Ultimately, the future of treasury is invisible—it will be a quiet, autonomous heartbeat that ensures a company always has exactly the capital it needs, exactly where it needs it.
