The Self Bank agent layer exists to provide selected platform capabilities through a controlled, machine-readable, sandbox-first model of integration. reduce uncertainty in technical assessment External teams need a clearer contract than just exploring through the UI. support low-risk exploration of capabilities Early integration should start with read access and simulations. separate controlled exposure from the internal complexity of the platform Not all internal services should be directly accessible to external consumers. prepare for future enterprise scenarios with agents Structured exposure of capabilities is a necessary prerequisite for broader machine integration. This layer is designed to enhance technical clarity, ensure controlled implementation, and prepare for future integration readiness.

Product discovery Onboarding flow simulation Payment validation simulation Analytics summary generation Account opening lifecycle simulation

Layer 01 — Consumers Corporate users, developers, and AI agents Layer 02 — Agent integration Self Bank agent layer Sandbox-first API, limited scope capabilities, controlled access Layer 03 — Platform services Self Bank platform services Products, onboarding, payments, analytics, account processes Layer 04 — Enterprise deployment and management Controlled enterprise deployment Governance, management, auditability, production deployment The Self Bank agent model is designed as a controlled integration layer between external consumers and selected platform capabilities. The current focus is on sandbox-first access, structured exposure of capabilities, and future enterprise governance.

The initial agent layer of Self Bank is focused on a small set of low-risk sandbox-first capabilities designed for controlled enterprise exploration. getProductCatalog Discovery of available product and service categories offered by Self Bank. simulateOnboarding Modeling the expected onboarding flow, document requirements, and verification process. simulatePayment Validation of payment structure and process behavior without actual movement of funds. simulateAccountOpening Simulation of lifecycle stages and checks for account opening applications. generateAnalyticsSummary Providing aggregated operational insights through a controlled summary model. These capabilities are intended for gradual implementation in the sandbox before controlled enterprise deployment.

The agent layer of Self Bank is designed for gradual implementation: starting with low-risk exploration in the sandbox and moving to controlled enterprise integration. Stage 01 Discovery of Capabilities Exploring the initial agent skills of Self Bank, scope model, and availability in the sandbox. Stage 02 Validation in Sandbox Testing scenarios for reading and simulations in a controlled environment. Stage 03 Integration Assessment Evaluating technical compliance, scope of permissions, governance requirements, and deployment constraints. Stage 04 Controlled Enterprise Deployment Expanding selected capabilities through an approved enterprise deployment model. This path ensures disciplined implementation, technical clarity, and enterprise trust. Control and Security Boundaries Enterprise-level isolation between agent surfaces and core banking systems. Sandbox-first Access Model No actual movement of funds in the sandbox No creation of real clients in the sandbox Controlled access based on scope of permissions Planned audit and governance model Production access only through controlled enterprise deployment

Through ESB/integration layer: payments and account requests are sent to the core, and responses are returned to the channels.

Yes, Self_Cube is designed as an intermediary platform that operates on top of any core banking system. Integration is carried out through an API gateway and does not require replacing the existing infrastructure. We support integration with major core systems: Temenos, Finacle, Flexcube, and local solutions.

Self_Cube complies with PCI DSS standards, ISO 27001, and regulatory requirements. The platform includes multi-factor authentication, data encryption, detailed audit logs, DDoS attack protection, integration with SIEM systems, and continuous threat monitoring. All components undergo regular security audits.

Yes, Self_Cube includes specialized modules for cryptocurrency and investment banks: custodial solutions, tokenization, anti-money laundering in blockchain, integration with exchanges, robo-advisory, portfolio management. The platform meets regulatory requirements for obtaining these types of licenses.

Typical timelines: MVP in 6–12 months, full implementation in 12–18 months. Costs depend on the scope of functionality, number of integrations, and scale. We offer several licensing models: license + implementation, SaaS subscription, profit share. Contact us to calculate the cost of your project.