Tilores Introduction
Tilores is a Berlin-based entity-resolution-as-a-service platform that helps data-driven companies unify, deduplicate, and connect scattered customer data across multiple systems in real-time through its highly scalable API.
View MoreWhat is Tilores
Tilores is a cutting-edge technology company that specializes in entity resolution, originally developed for consumer credit bureau use in eCommerce risk and fraud prevention. Founded by Stefan Berkner, Hendrik Nehnes, and Steven Renwick in Berlin, the company offers a serverless, graph-like technology that transforms how organizations handle disparate and inconsistent datasets. The platform serves as a comprehensive solution for data scientists and data-driven companies who need to manage, clean, and unify customer data efficiently without compromising on scalability or speed.
How does Tilores work?
Tilores operates through a globally distributed GraphQL API that connects to various source systems, including pre-built connectors for platforms like Salesforce, Hubspot, and Snowflake. The system first cleanses, normalizes, and enriches customer data to match a unified schema before ingestion. It then employs advanced entity resolution technology to identify and link related records, creating a unified customer view across all connected systems. The platform maintains data synchronization across all source systems, making each system a distributed source of truth. Additionally, Tilores integrates with LLMs (Large Language Models) for enhanced data retrieval and context-aware querying, supporting features like Retrieval-Augmented Generation (RAG) for improved AI applications.
Benefits of Tilores
Organizations using Tilores can significantly reduce manual data processing time, with some customers reporting up to 99% decrease in manual customer credit decisions. The platform enables real-time fraud detection at account creation, improves customer service through unified 360° customer views, and enhances internal reporting accuracy. Its automated synchronization eliminates engineering complexity and overhead costs, while maintaining transparency in data matching decisions. The system's scalability allows businesses to handle both historical and new customer data efficiently, making it easier to build new use cases and applications without dedicated development resources. Furthermore, its compliance with data privacy regulations and robust security measures ensure safe handling of sensitive customer information.
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