As enterprises grapple with fragmented data, multiple banking relationships and increasingly complex financial operations, AI is emerging as a powerful enabler of faster and more informed decision-making. Bengaluru-based Zenalyst is positioning itself at the forefront of this transformation through its AI-driven enterprise intelligence and treasury management platform. In this interaction, Nagendra Singh, CEO, Zenalyst, discusses how the company is leveraging AI to deliver real-time cash visibility, automate treasury operations and help real-estate developers make smarter financial decisions.What inspired the launch of Zenalyst and what financial visibility challenges were you trying to address for real-estate developers?When we were on the other side of the table, working as financial controllers and CFOs, we realised that critical reports and cash balances were often available only after two days. We wanted to solve this problem by providing real-time cash visibility and accurate forecasting.Real-estate companies typically operate multiple entities and maintain several bank accounts because of RERA compliance. Some of our clients have 600 to 1,000 bank accounts. Consolidating and managing transactions across these accounts manually is almost impossible, even with large teams. This is where AI becomes essential. We connect with banks, consolidate transactions and use AI to understand every transaction as a business event, giving companies a single view of their finances.Is Zenalyst primarily a treasury management platform?Treasury management is one of our flagship products but we are fundamentally an AI innovation company. We help organisations make better decisions. Treasury is only one aspect. We support decisions related to investments, spending, project planning and overall business performance. You can think of it as smart money management and intelligent decision-making.How does Zenalyst create a unified, real-time view across multiple SPVs, escrow accounts and banking relationships?We connect directly with banks through APIs. Where APIs are unavailable, particularly with some public-sector banks, we establish host-to-host connectivity. We also integrate with ERP systems such as SAP, CRM platforms, OneDrive, Gmail, Oracle NetSuite, Salesforce and many other systems. We currently have over 200 connectors. Once the data is connected, AI works on top of it, enabling organisations to view and manage all their information from a single platform.Indian banking systems, especially PSU banks, are often considered rigid. Have you faced resistance while integrating with them?RBI mandated banks to provide APIs several years ago. Most banks are trying to improve their technology capabilities because convenience has become a competitive advantage. Private banks such as ICICI Bank, Kotak Mahindra Bank, YES Bank and IDFC First Bank are doing very well. Public-sector banks such as SBI and PNB are still evolving, but they are also moving quickly because technology is increasingly influencing business decisions. Compared with many global markets, India is actually in a strong position. The US and the Middle East are very advanced, and India ranks among the better markets in terms of banking connectivity.How does Zenalyst use AI for reconciliation, forecasting, compliance and cash-flow planning while ensuring data security and governance?Security is a top priority for us. We are ISO 27001 certified and are also pursuing SOC 2 compliance. Our clients include highly sensitive sectors, where security requirements are extremely stringent. The entire client data resides either on the client’s Cloud infrastructure or on their own servers. We do not store client data on our systems. We have a three-layer architecture comprising the data layer, application layer and AI layer. The data and application layers remain with the client, while our AI layer operates with masking protocols to ensure that sensitive information is protected. We also implement role-based access controls, ensuring that users access only the information relevant to them.How does AI improve reconciliation and collections management?AI reads bank narrations and automatically identifies the nature of every transaction – whether it is a payment, receipt, loan, interest or customer collection. For collections, AI monitors project milestones through CRM and engineering certificates. Once a milestone is achieved, it can automatically trigger customer communications through WhatsApp, emails or calls. It can even respond to customer queries, validate payment screenshots and reconcile transactions using UTR numbers. On the borrowing side, AI can read sanction letters, facility agreements and escrow agreements. It tracks covenants, liquidity ratios and account balances, and sends alerts to CFOs and treasury teams if there is a risk of non-compliance or penalties.How accurate are your forecasting capabilities?Forecasting in real estate depends on several variables, including collection efficiency, sales efficiency, construction progress and vendor payment schedules. Since our platform is integrated with ERP systems, it can analyse all these parameters and deliver highly realistic forecasts.We can achieve forecasting accuracy of around 95 to 99 per cent for short-term cash flows, enabling companies to understand how much money they will receive, spend or have available over the next few days.Could you share an example of the impact Zenalyst has delivered for clients?One major impact is automation. In one implementation, a client reduced the team handling treasury operations from 20-25 people to just two. More important, real-time visibility enables companies to identify idle cash and deploy it more efficiently. One of our clients manages a treasury of around Rs.70 billion. Through better visibility and cash deployment, they were able to generate significant savings. Most clients recover their investment in our platform within a month because the return on investment is immediate.How do you see AI, particularly agentic AI and predictive analytics, reshaping treasury management in coming years?Organisations that do not adopt AI will inevitably fall behind. Every major technology shift – from computers to Cloud computing – has transformed how businesses operate. AI represents the next such transformation. Today, AI enables organisations to analyse information in real time, not only from internal systems but also from external events. For example, geopolitical developments, disruptions in global markets or changes in commodity prices can all influence financial decisions. AI can identify these developments early and alert decision-makers.Ultimately, AI will transform every business decision by making it faster, more accurate and more data-driven.