DataKite AI Digital Twin is built in collaboration with banks for the banks

The DataKite AI Digital Twin is a groundbreaking solution designed to revolutionize retail banking by creating a comprehensive, AI-driven digital twin of your bank's data ecosystem. By seamlessly importing all critical databases, from CRM and core banking to credit cards and loans, the DataKite AI Digital Twin transforms complex relationships into a FIBO-compliant knowledge graph. This innovative approach converts all data and relationships into a property graph database, providing a powerful foundation for a wide range of AI applications.

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With the DataKite AI Digital Twin, banks can unlock new levels of operational efficiency, enhance customer insights, and drive personalized engagement strategies. The solution offers robust data governance frameworks, admin control, authority matrices, and audit trails, ensuring compliance and data security at every step. By leveraging sandbox graph databases and advanced data synthesizers, banks can model various scenarios, optimize decision-making, and stay ahead of the competition.

DataKite AI Transformer

It all starts with the DataKite AI Transformer, which is a sophisticated data processing engine built on a Large Language Model (LLM) specifically trained on Financial Industry Business Ontology (FIBO) terms. This advanced GenAI transformer serves as the core engine for reading, interpreting, and converting data from multiple retail banking databases into a unified property graph database.

Master Graph Database

The Master Graph Database is the central hub within the DataKite AI Digital Twin architecture that stores the integrated, transformed, and enriched data from various retail banking databases. This repository is built using a property graph model, which represents data as nodes, edges, and properties, allowing for complex relationships and hierarchies to be easily stored and queried.

Core Banking Simulator

The Core Banking Simulator is a critical component within the DataKite AI Digital Twin that acts as a verification tool to ensure data consistency and integrity across all integrated databases. Its primary function is to consolidate data from various sources, validate it against the core banking system, and produce discrepancy reports if any data mismatches are detected. By doing so, it ensures that all data representations align with the authoritative records maintained in the core banking database.

Data Governance Framework

The Data Governance Framework is a comprehensive set of roles, policies, processes, and tools designed to manage and control the data assets within the DataKite AI Digital Twin. This framework establishes the standards and protocols necessary to ensure data is managed responsibly, securely, and in compliance with industry regulations. It provides a structured approach to data management, enhancing the quality, integrity, and usability of data across the organization.

Admin Control

The Admin Control component is the central management hub of the DataKite AI Digital Twin, providing administrators with the tools and capabilities needed to monitor, manage, and maintain the entire digital twin environment. This component is designed to ensure the smooth operation of the Digital Twin, enhance system security, enforce policies, and facilitate effective data governance.

Authority Matrix & Audit Trail

The Authority Matrix & Audit Trail is a key component within the DataKite AI Digital Twin that ensures strict control and monitoring of data access and modifications. This framework defines who has the authority to perform specific actions within the system, while maintaining a comprehensive record of all activities, interactions, and data changes. This ensures accountability, enhances data security, and supports regulatory compliance.

Sandbox Manager

The Sandbox Manager is a powerful feature within the DataKite AI Digital Twin that provides a secure and isolated environment where data scientists, analysts, and business leaders can experiment with various AI models, data simulations, and algorithms without affecting the live production environment. This component ensures that banks can innovate and test new strategies while maintaining data integrity, security, and compliance.

Data Synthesizer

The Data Synthesizer is a key component of the DataKite AI Digital Twin platform, designed to generate synthetic datasets by removing or masking personally identifiable information (PII) from the Master Graph Database. It enables banks to securely share and experiment with data both internally and with third-party vendors without compromising customer privacy or violating regulatory compliance standards. The Data Synthesizer is essential for facilitating AI application development and testing in a controlled, compliant, and secure environment.

SKYE – Conversational Data Intelligence Assistant

The Data Synthesizer is a key component of the DataKite AI Digital Twin platform, designed to generate synthetic datasets by removing or masking personally identifiable information (PII) from the Master Graph Database. It enables banks to securely share and experiment with data both internally and with third-party vendors without compromising customer privacy or violating regulatory compliance standards. The Data Synthesizer is essential for facilitating AI application development and testing in a controlled, compliant, and secure environment.