AI Apps Tilores Identity RAG

Tilores Identity RAG: Streamlining LLMs with Integrated Customer Data

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Tilores Identity RAG

Tilores Identity RAG

Enhances LLMs with unified, real-time customer data retrieval.

Tilores Identity RAG

Overview of Tilores IdentityRAG: Enhancing LLMs with Unified Customer Data Retrieval

Tilores IdentityRAG is a specialized tool designed to augment Large Language Models (LLMs) by providing them with the ability to search and retrieve customer data from multiple source systems. This service is particularly useful for data scientists and developers who need to integrate comprehensive customer insights into AI-driven applications.

Key Features

Data Unification

  • Unified Data Access: Tilores IdentityRAG consolidates scattered customer data from various systems, allowing LLMs to access a complete view of customer information.
  • Real-Time Updates: Changes in any connected data source are immediately reflected, ensuring that the LLM operates with the most current data available.

Advanced Identity Resolution

  • Robust Matching Algorithms: The service employs sophisticated algorithms to match customer profiles based on various identity attributes such as name, address, date of birth, email, and phone number.
  • Accurate Customer Profiles: Generates dynamic, accurate customer profiles at query time, enhancing the relevance and precision of the LLM's outputs.

Integration and Scalability

  • LangChain and Bedrock Integration: Tilores uses leading frameworks like LangChain and Amazon's Bedrock service to seamlessly integrate with LLMs.
  • Serverless Infrastructure: Offers a managed, serverless infrastructure that scales automatically without requiring manual maintenance.

Use Cases

  • Risk and Fraud Management: Enables quicker and more accurate detection of potential risks and fraudulent activities by providing a holistic view of customer activities across platforms.
  • Customer 360° View: Assists businesses in achieving a comprehensive understanding of their customers, enhancing personalization and customer service efforts.

Practical Application

The application demonstrates its capabilities through a simulated environment where users can interact with a chatbot named Tilo. Tilo accesses customer data from integrated systems like Salesforce, HubSpot, Zendesk, Mailchimp, and various loan databases to respond to queries about customer profiles, support issues, loan balances, and marketing engagements.

Developer Tools and Resources

  • Fuzzy Matching Tools: Helps in identifying non-exact matches among data entries.
  • Geocoding API: Useful for applications requiring location-based data integration.
  • Text Normalization Tool: Standardizes text data to enhance matching accuracy.
  • Documentation and GitHub Repositories: Provides comprehensive resources for developers to integrate and utilize the service effectively.

Tilores IdentityRAG is designed to be a robust backend service for applications requiring access to unified and real-time customer data, enhancing the capabilities of LLMs in various business contexts.

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