FintechOS has launched its Data Core product on Google Cloud Marketplace, expanding its collaboration with Google Cloud for agentic AI in financial services.
The move targets a structural challenge that has constrained enterprise AI adoption in financial services: fragmented data. Customer and product data in financial institutions typically resides across core banking and insurance systems, CRMs, line-of-business platforms, risk and underwriting engines, and third-party ecosystem providers. Without a unified view, AI agents either operate on incomplete context, producing unreliable outputs, or require multi-year data consolidation programmes before deployment can begin.
Virtualised access without physical migration
Data Core addresses this by ingesting data from internal systems, (including core banking, core insurance, wealth platforms, CRMs, and line-of-business tools) as well as external sources such as third-party risk engines, underwriting providers, KYC, and fraud data services. Rather than requiring physical data consolidation, the product virtualises access through a unified semantic layer and exposes governed Data Products that AI agents, workflow engines, and the FintechOS Dex copilot can operate against.
The semantic layer is aligned to BIAN (Banking Industry Architecture Network) service domain definitions and ACORD (Association for Cooperative Operations Research and Development) data standards, two reference models widely used by banks and insurers to structure their operations. Policy enforcement, data lineage, and access controls are applied at runtime rather than added as a separate layer.
Data Core is one of three components of the FintechOS 8 platform, alongside a Unified Product Operations Engine and Agentic Workflow Orchestration. The platform is aligned to the FINOS AI Governance Framework and holds SOC 2 Type 2 attestation.
Procurement and compliance implications
Listing on Google Cloud Marketplace allows financial institutions to procure Data Core through their existing Google Cloud relationship, consolidating billing onto a single invoice and applying spend towards existing Google Cloud committed use agreements. This structure is intended to reduce procurement and legal cycle times, which can delay enterprise software deployments in regulated environments. Larger deployments are available through Google Cloud Marketplace Private Offers, with negotiated pricing and contract terms.
In addition, customers deploying via Google Cloud also inherit the cloud provider's security, data residency, and compliance controls, a relevant consideration for financial institutions operating under audit and deployment constraints across multiple jurisdictions.
The platform's compounding data model means that operational data generated as customers configure products, orchestrate workflows, and log decisions becomes resident within the platform and reusable over time, progressively expanding the governed data foundation available to AI agents.
