

Identityrag
Overview :
IdentityRAG is a tool designed for constructing LLM chatbots based on customer data that can retrieve unified customer information from multiple internal source systems such as databases and CRMs. The product processes spelling errors and inaccuracies through real-time fuzzy search, providing accurate, relevant, and unified customer data responses. It supports rapid retrieval of structured customer data, builds dynamic customer profiles, and updates customer information in real-time, allowing LLM applications to access unified and accurate customer data. IdentityRAG is trusted by rapidly growing, data-driven enterprises for its quick response, real-time data updates, and ease of scalability.
Target Users :
The target audience for IdentityRAG includes rapidly growing, data-driven enterprises, particularly those that need to handle and analyze vast amounts of customer data to provide personalized services and optimize business processes. This product is well-suited for companies looking to build LLM chatbots based on customer data, helping them enhance customer service quality and operational efficiency.
Use Cases
US Voter Fraud: Utilizing IdentityRAG to process data on voter fraud in the United States.
UK Companies House: Using IdentityRAG to manage data on UK company registrations.
CRM Deduplication: Implementing IdentityRAG for deduplicating CRM data.
Features
Real-time fuzzy search: Handles spelling errors and inaccuracies, enhancing LLM performance.
Data unification: Employs fuzzy matching techniques to unify customer data from different source systems, even when attributes are not identical.
Rapid retrieval of structured customer data: Builds dynamic customer profiles and provides real-time access to unified and accurate customer data.
Real-time updates: Any updates to customer data in source systems are instantly reflected in LLM applications.
Quick launch: Start quickly with LangChain integration and data connectors without requiring maintenance.
Scalability: Use managed and distributed infrastructure to scale customer data according to LLM growth.
How to Use
1. Visit the IdentityRAG official website and register for an account.
2. Utilize the LangChain integration to access IdentityRAG on GitHub.
3. Create a Tilores account at app.tilores.io and obtain a free API key.
4. Build LLM applications based on IdentityRAG according to the official documentation and guidelines.
5. Leverage IdentityRAG's API to unify customer data scattered across different systems.
6. Enhance LLM performance and response accuracy through real-time fuzzy search and data unification techniques.
7. Monitor and update customer data to ensure that the information in the LLM application is current.
8. Expand the scope and scale of IdentityRAG applications based on business needs.
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