Tilores

Tilores: Real-Time Customer Data Unification API

Overview:

Tilores is an API designed to unify scattered customer data across multiple source systems in real-time. By consolidating data into a single, comprehensive customer profile, businesses can enhance risk management, detect fraud, deliver personalized digital experiences, and support Generative AI (GenAI) applications without extensive engineering efforts. ​

Key Features:

Customer 360 View: Combines disparate and siloed customer data into a unified profile, which can be synchronized across all departmental systems to improve customer service, align internal teams, and inform product development. ​

Real-Time Risk & Fraud Management: Detects fraudulent activities during account creation by matching new sign-ups against existing customer data streams, uncovering relationships with other account holders. ​

Retrieval-Augmented Generation (RAG): Enhances Large Language Models (LLMs) by providing real-time fuzzy search on structured data, enabling accurate and relevant responses with greater context. ​

Automated Data Synchronization: Ensures that unified customer data is automatically synced back to each department's source system, maintaining consistency and up-to-date records across the organization. ​

Transparent Data Merging: Provides clear justification for each data merge or relationship mapped, allowing businesses to understand and adjust unification parameters to align with their specific needs. ​

Benefits:

Scalability: Capable of unifying both new and historical customer data, supporting the development of various use cases on top of the unified data. ​

Efficiency: Reduces the time and engineering complexity associated with data unification, enabling internal departments to report and build on customer data independently. ​

Enhanced Decision-Making: Provides a comprehensive view of customer data, facilitating informed decisions in risk management, fraud detection, and personalized customer engagement. ​

Use Cases:

Customer 360 View: Creates a single unified view of customers by combining data from different source systems, aiding in personalized experiences and improved customer service. ​

Real-Time Risk & Fraud Verification: Detects fraud at account creation by querying a real-time stream of unified customer data to match new sign-ups to existing customers or uncover their relationships with other account holders. ​

Retrieval-Augmented Generation (RAG): Upgrades LLM performance by using real-time fuzzy search on structured data, enabling the retrieval of accurate, relevant, and unified customer or company data for more context-aware responses.