Elevate your Generative AI Solution with Reasoning

Reasoning allows AI systems to analyze information, draw conclusions, and make decisions based on logical inference and evidence. It involves understanding relationships between different pieces of data, identifying patterns, and using logical rules to reach conclusions or solve problems.

At Lynx Analytics, we combine reasoning with Large Language Models (LLMs) to significantly enhance the capabilities of Generative AI solutions. LLMs excel at understanding and generating natural language text. By integrating reasoning capabilities into LLMs, we give them the ability to not only generate text but also to reason about it. This integration enables our AI systems to understand context, infer relationships, and generate responses that are more coherent and contextually appropriate.

Using Graph AI to Enhance Reasoning Capabilities

Graph AI excels in mapping out complex relationships within networks, utilizing nodes and edges to represent and predict intricate dynamics. By integrating Graph AI with machine learning, we significantly improve our reasoning solutions, offering clearer and more impactful analyses. Our unique approach marries machine learning, Graph AI, and large language models to not only uncover but also forecast and elucidate the evolving dynamics in networks like medical knowledge graphs or key opinion leader networks. This ensures our AI systems are adept at reasoning, providing insights, and suggesting informed next steps.