Tilores

Tilores is an API-driven solution that is intended to unify fragmented consumer data in real time. It assists businesses in the enhancement of decision-making, the detection of fraud, the management of risks, and the delivery of personalized digital experiences. By offering a centralized yet distributed customer data management system, it eliminates the necessity for considerable engineering and guarantees the accuracy and accessibility of data.

Features of Tilores:

• Customer 360� View: Improves operational efficiency and service delivery by consolidating fragmented customer data into a unified profile.
• Real-Time Data Unification: Employs a scalable API to combine historical and new customer data for real-time management and application development.
• Risk and Fraud Management: By comparing new accounts to extant customer data streams, fraudulent sign-ups are identified.
• Retrieval-Augmented Generation (RAG): Improves data retrieval accuracy by enhancing the performance of the Large Language Model (LLM) through real-time fuzzy search.

Positives:

• Time Efficiency: Decreases the time required for manual data processing, resulting in a 99% reduction in the time required for credit decision-making.
• Scalability: Facilitates the unification of large-scale data without the addition of additional engineering complexity, thereby accommodating the expanding requirements of businesses.
• Transparency: Guarantees data clarity by providing a clear rationale for profile merges and relationship mapping.
• Automated Syncing: Ensures the integrity of data by automatically syncing unified consumer data with source systems.

Negatives:

• Initial Setup Complexity: In order to effectively integrate multiple source systems, technical expertise is necessary.
• Limited Third-Party Integration: Supports major platforms such as HubSpot and Salesforce; however, niche systems may be subject to limitations.
  -- Learning Curve: It may take some time for users to become accustomed to the platform's extensive capabilities.

• Financial Institutions: Improving fraud prevention and credit risk assessment.
• Retail Businesses: Enhancing consumer experiences through personalized digital interactions.
• Insurance Companies: Optimizing risk management and customer profiling.
• Telecommunications Providers: Streamlining customer data to enhance service delivery and reporting.
• Educational Institutions & Non-Profit Organizations: Consolidating donor data for analysis and teaching data management courses.