Plumery, a digital banking development platform for customer-centric banking, has released AI Fabric, which creates an artificial intelligence (AI)-ready foundation for AI-assisted digital banking. The new solution addresses one of the most pressing challenges facing financial institutions today: how to move beyond AI pilots and experiments to deploy production-ready AI systems that improve customer experience and operations while maintaining the governance, security, and regulatory compliance that banking requires.
Based on an event-driven data mesh architecture, the new solution gives financial institutions a standardised way to connect AI and generative AI (GenAI) models and agents to banking data, eliminating the need for bespoke system integrations. AI Fabric moves institutions away from brittle point-to-point architectures towards an event-driven, API-first architecture that scales with innovation, providing a foundation that can evolve as AI capabilities and business requirements change over time.
Most financial institutions struggle to operationalise AI because their data is fragmented across legacy cores, channels, and point-to-point integrations. Each new AI pilot can require fresh plumbing, security reviews, and governance work, which delays time-to-value and increases risk. This fragmentation means that AI initiatives often start from scratch, with teams spending months building custom data pipelines and integration layers before they can even begin testing AI models or delivering value to customers.
In addition, under increasing regulatory pressure, institutions are required to explain, audit, and govern AI decisions. Regulators across multiple jurisdictions have made clear that financial institutions must be able to demonstrate how AI systems make decisions, particularly in areas like credit scoring, fraud detection, and anti-money laundering. Together, these factors make ad-hoc approaches to AI difficult to scale, leaving many institutions stuck in a cycle of pilots and proofs of concept that never reach production.
Plumery's AI Fabric enables institutions to plug in and swap AI capabilities as the ecosystem evolves. It exposes high-quality, domain-oriented banking events and data streams in a consistent, governed, and reusable way across products, channels, and customer journeys. This means that once the foundation is in place, institutions can deploy new AI use cases much more quickly, reusing the same data infrastructure and governance frameworks rather than building custom solutions for each initiative.
Importantly, the platform separates systems of record from systems of engagement and intelligence, giving financial institutions long-term agility instead of short-lived AI experiments. This architectural separation means that institutions can innovate in their customer-facing channels and AI-powered services without risking the stability of their core banking systems, while still maintaining real-time access to the data and events that AI systems need to deliver value.
By reducing point-to-point integrations and one-off data pipelines, an institution can lessen operational complexity and technical debt. This makes change cheaper, safer, and more predictable, enabling institutions to respond more quickly to competitive pressures, regulatory changes, and evolving customer expectations. Additionally, having clear data lineage, ownership, and control makes it easier to explain decisions, manage model risk, and satisfy regulators, reducing compliance friction as AI adoption grows.
Ben Goldin, Founder and CEO of Plumery, emphasized that financial institutions have clear requirements for AI deployment: "Financial institutions are clear about what they need from AI. They want real production use cases that improve customer experience and operations, but they will not compromise on governance, security, or control. Our AI Fabric gives them a standard, bank-grade way to allow AI use within their tools and data without rebuilding integrations for every model."
Goldin explained that the event-driven data mesh architecture represents a fundamental shift in how banking data is managed: "The event-driven data mesh architecture improves the process by changing how banking data is produced, shared, and consumed, rather than adding another AI layer on top of fragmented systems." This approach addresses the root cause of AI operationalisation challenges rather than simply adding more technology to work around existing limitations.
In today's fast-changing world, financial institutions need an AI foundation that absorbs change instead of amplifying it. With AI Fabric, institutions can experiment, deploy, and evolve AI-assisted use cases incrementally without re-architecting every time a model, vendor, or requirement changes. This flexibility is critical in an environment where AI technology is evolving rapidly, with new models and capabilities emerging regularly that can deliver significant competitive advantages.
Additionally, operational, customer, and risk decisions can be powered by live banking events rather than delayed, batch-based snapshots. This enables AI to assist where it matters most: in-journey, in-context, and in-the-moment. For example, AI systems can provide real-time recommendations during customer interactions, detect fraud as transactions occur, or adjust credit decisions based on the most current information available, rather than relying on data that may be hours or days old.
Even financial institutions not yet ready to operationalise AI can lay the groundwork today with AI Fabric, ensuring they can move quickly and safely when priorities, budgets, or markets shift. This forward-looking approach enables institutions to build the foundation for AI adoption without committing to specific use cases or technologies, providing flexibility to respond to changing business conditions and competitive dynamics.
The challenge that AI Fabric addresses is well-documented in the financial services industry. Research by McKinsey suggests that while generative AI could materially improve productivity and customer experience in financial services, most banks struggle to translate pilots into production because of fragmented data estates and incumbent operating models. The consultancy argues that enterprise-level AI adoption requires shared infrastructure and governance, and reusable data products—precisely what Plumery's AI Fabric aims to provide.
The platform's event-driven architecture is particularly significant for financial institutions. Traditional batch-based data processing creates delays between when events occur and when AI systems can respond to them, limiting the effectiveness of AI in time-sensitive applications like fraud detection, customer service, and real-time personalization. By processing banking events as they occur and making them immediately available to AI systems, AI Fabric enables institutions to deploy AI capabilities that can respond in real-time to customer needs and business events.
The data mesh architecture that underlies AI Fabric represents a modern approach to data management that is gaining traction across industries. Rather than centralizing all data in a single data warehouse or data lake, a data mesh distributes data ownership to domain teams while providing standardized interfaces and governance frameworks. This approach aligns well with the organizational structure of most financial institutions, where different business units own different products and customer relationships, while still enabling the cross-functional data access that AI systems require.
For financial institutions, the governance and auditability features of AI Fabric are particularly important. Regulators have made clear that institutions must be able to explain how AI systems make decisions, particularly in areas that affect customers like lending, pricing, and fraud detection. By providing clear data lineage and tracking how data flows from source systems through AI models to business decisions, AI Fabric helps institutions meet these regulatory requirements while still enabling the innovation that AI makes possible.
The platform's ability to support multiple AI models and vendors is also strategically important. The AI landscape is evolving rapidly, with new models and capabilities emerging regularly. Institutions that build custom integrations for specific AI vendors or models risk being locked into technologies that may become obsolete or uncompetitive. By providing a standardized integration layer, AI Fabric enables institutions to experiment with different AI capabilities and switch between vendors as the technology evolves, without rebuilding their entire AI infrastructure.
Plumery's launch of AI Fabric comes at a time when the company is gaining recognition in the digital banking space. The Amsterdam-based company made its Finovate debut at FinovateEurope 2025 in London, where it demonstrated its Super App Accelerator, which empowers financial institutions to launch comprehensive Super Apps within weeks. The company has also been recognized with multiple industry awards, including Ben Goldin's nomination for Visionary Founder at the Banking Tech Awards 2025.
The AI Fabric platform reflects broader trends in financial services technology, where institutions are increasingly seeking composable architectures that allow them to integrate best-of-breed capabilities rather than relying on monolithic systems. This approach enables faster innovation and greater flexibility, while still maintaining the stability and governance that banking requires. By providing a standardized foundation for AI integration, Plumery is positioning itself as a key infrastructure provider for the next generation of digital banking.
For the broader financial services industry, the launch of AI Fabric represents an important step toward making AI more accessible and practical for institutions of all sizes. While the largest banks have the resources to build custom AI infrastructure, smaller institutions often struggle to operationalise AI because of the complexity and cost involved. By providing a standardized platform that reduces the integration and governance burden, Plumery is helping to democratize access to AI capabilities across the financial services sector.
The platform also addresses a critical gap in the market. While there are many AI model providers and many core banking system vendors, there are relatively few solutions that focus specifically on the integration and governance layer between these systems. This integration layer is often where AI initiatives fail, as institutions struggle to connect AI models to banking data in a way that is secure, governed, and scalable. By focusing on this critical layer, Plumery is addressing a key bottleneck in AI adoption.
Looking ahead, the success of AI Fabric will depend on Plumery's ability to demonstrate that the platform can deliver on its promise of faster, safer AI deployment. Financial institutions are understandably cautious about adopting new infrastructure, particularly for mission-critical capabilities like AI. However, the clear need for better AI operationalisation tools, combined with Plumery's growing track record in digital banking innovation, suggests that AI Fabric could play an important role in accelerating AI adoption across the financial services industry.