RAG & LLMs
Science & Technology
Introduction
Equitus AI's Advanced Knowledge Graph (KGN) offers a range of dynamic capabilities to meet your organization's needs. Leveraging retrieval augmented generation (RAG) and large language models (LLMs), Equitus AI utilizes its KGN to significantly enhance the accuracy and relevance of outputs while combating hallucinations and inaccuracies that are common with LLMs.
By efficiently representing relationships and entities, the KGN facilitates precise querying and retrieval of interconnected data points. This real-time contextualization with domain-specific company data vastly improves the effectiveness of responses. KGN's strengths make it especially well-suited for enterprise use cases including semantic search, content generation, and co-pilots, ensuring that outputs are trustworthy and based on accurate, up-to-date information.
Keywords
- Advanced Knowledge Graph (KGN)
- Retrieval Augmented Generation (RAG)
- Large Language Models (LLMs)
- Entity Representation
- Precise Querying
- Real-Time Contextualization
- Enterprise Use Cases
- Semantic Search
- Content Generation
- Co-Pilots
- Accuracy
- Relevance
FAQ
What is the Advanced Knowledge Graph (KGN)?
The Advanced Knowledge Graph (KGN) is a system used by Equitus AI to represent relationships and entities efficiently for the purpose of enhancing data retrieval and output accuracy.
How does KGN improve large language models (LLMs)?
KGN enhances LLMs by providing accurate, real-time contextual data which helps in combating hallucinations and inaccuracies in LLM outputs.
What are some enterprise use cases for KGN?
KGN is particularly well-suited for use cases such as semantic search, content generation, and co-pilots, ensuring accurate and up-to-date information.
What is retrieval augmented generation (RAG)?
Retrieval Augmented Generation (RAG) is a technique used to improve the efficiency and relevance of data retrieval by augmenting it with real-time data from a knowledge graph.
How does KGN ensure the trustworthiness of its outputs?
KGN ensures trustworthiness by basing outputs on accurate, up-to-date information through precise querying and real-time contextualization with domain-specific data.