Tilores Features
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 MoreKey Features of Tilores
Tilores is a highly-scalable entity resolution platform that helps companies unify and manage scattered customer data across multiple source systems in real-time. It offers automated data cleaning, matching, and deduplication capabilities while maintaining data privacy compliance. The platform provides a no-code interface and API integration options, allowing businesses to create unified customer views, prevent fraud, and power AI applications without complex engineering requirements.
Real-time Data Unification: Performs live searches, linking and normalization of data as it arrives from different source systems, creating a unified customer view
Privacy-Compliant Architecture: Built with data privacy at its core, ensuring compliance with data protection regulations while handling sensitive customer information
Automated Data Management: Offers automated data cleaning, matching, and deduplication capabilities with clear reasoning for each profile merge or relationship mapped
Flexible Integration Options: Provides GraphQL API and pre-built connectors for various platforms like Salesforce, Hubspot, and Snowflake
Use Cases of Tilores
Customer 360° View: Enables businesses to create complete customer profiles by combining data from multiple sources, improving customer service and internal alignment
Risk & Fraud Management: Helps detect fraud at account creation by matching new sign-ups with existing customer data and uncovering relationships between account holders
LLM Enhancement: Improves LLM performance through real-time fuzzy search on structured data, enabling more accurate and contextual responses
Regulatory Compliance: Supports KYC & AML compliance requirements by maintaining accurate and unified customer records
Pros
No-code platform makes it accessible for non-technical users
Highly scalable architecture suitable for large datasets
Real-time processing capabilities
Clear transparency in data matching decisions
Cons
CLI does not support Windows systems
UI changes may not be immediately reflected in documentation
Requires redeployment for schema or rule changes
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