Techblogs

  Introduction With the boom of AI and autonomous agents, we’ve already seen disruption across industries from automating engineering workflows to drafting legal contracts to handling customer support. And now, there’s a not-so-silent shift happening in the payments landscape. Agent-led commerce is no longer a futuristic idea; it’s already here. Analysts estimate that by 2030,  up to 30% of digital transactions could be initiated by AI agents rather than humans.  That’s billions of payments annually happening without a human ever clicking “Buy.”. For businesses, this is not just a technological shift—it’s a new competitive battleground. Those who adapt early will unlock new revenue streams and more efficient business models, while those who don’t risk being left behind. What is Agent-Led Commerce? Agent-led commerce, in simple terms, is when an AI agent makes a purchase on behalf of the human. Read more

  Data silos are a silent barrier in many organizations, where isolated pockets of information reside across departments, systems, or platforms. This fragmentation makes it difficult for businesses to access the complete picture, leading to missed opportunities, inefficient workflows, and delayed decisions. Eliminating these silos is no longer just an operational challenge—it’s a strategic necessity. To move forward, organizations need a unified, accessible data ecosystem that enables faster, smarter decision-making. The  DataNimbus Platform  is designed to help businesses do just that, integrating data from multiple sources into one cohesive system for a more connected, agile, and insightful approach to operations. Understanding Data Silos: What Are They and Why Do They Matter? Data silos refer to isolated pockets of data spread across various systems and departments, preventing effective data sharing and collaboration. Data silos occur when different departments, system...

  Imagine navigating a complex maze without a clear map—regardless of your expertise or the advanced tools at your disposal, you’re bound to encounter dead ends, wasted effort, and missed opportunities. This scenario mirrors the experiences of many organizations implementing artificial intelligence without robust data governance and quality frameworks. Without clear guidelines and accurate, high-quality data, AI projects often fail to deliver their promised value, no matter how innovative the technology or skilled the team. The Hidden Challenge Behind AI Implementation The promise of artificial intelligence continues to captivate business leaders across industries, yet a troubling pattern has emerged beneath the surface of many ambitious initiatives. In today’s competitive landscape, organizations frequently invest millions in cutting-edge algorithms and data science talent only to discover their AI initiatives producing unreliable results. Behind these challenges often lies not th...

  [Dallas, 9 September 2025]  — DataNimbus , a leader in AI-powered  products and services , is pleased to announce the appointment of  Victor Cheah  as  Senior Vice President, Professional Services . With over two decades of experience in driving technology-enabled outcomes, Victor brings a proven track record of building high-performing global services teams and delivering large-scale transformation programs across industries and geographies. Prior to joining DataNimbus, Victor held senior leadership roles at  Databricks, Splunk, and BMC Software , where he consistently enabled customer success by operationalizing business predictability, scaling professional services organizations, and leading multi-million-dollar programs across North America, Latin America and Asia Pacific. At DataNimbus, Victor will lead the  Professional Services Organization , focusing on: Accelerating customer adoption of DataNimbus’  Data + AI  applications and...

 And how DataNimbus FinHub Ledgers helps you automate sub-accounting, control compliance, and scale financial operations. Today’s finance leaders oversee operations that move faster and span wider than ever before. A CFO may be tracking budgets across multiple business units, while the operations team ensures smooth payouts to vendors, manages branch-level flows, and keeps every transaction aligned with compliance. In high-volume, high-velocity environments — from marketplaces with thousands of merchants, to lenders disbursing funds in real time, to escrows with dynamic multi-party agreements — the traditional single-account structure often limits visibility and flexibility. What’s needed is an approach that provides granularity, programmability, and confidence at every level of financial activity. That’s where sub-accounting comes in — serving as the foundation that gives modern organizations the clarity and control they need to scale. Why Sub-Accounting Matters (More Than You Thi...

 In today’s fast-moving digital landscape, organizations rely on data pipelines to power dashboards, fuel machine learning models, and unlock actionable insights. However, pipeline development often presents challenges related to speed, reusability, and governance, particularly as teams expand. Databricks offers a powerful foundation for scalable data processing and advanced analytics. What teams need next is a way to standardize pipeline development while enabling customization and faster delivery, without increasing complexity. Why Traditional Data Pipelines Struggle with Scale and Agility Traditional data engineering pipelines often hit a wall when organizations need to scale. These pipelines are typically code-heavy, requiring specialized programming skills that create bottlenecks in team workflows. When team members change, these custom-built pipelines become maintenance nightmares, with tribal knowledge walking out the door. Additionally, most traditional pipelines lack reusa...