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As companies seek to simplify data access for employees and customers, AI is increasingly being used. However, there is a concern about setting up AI bots and Language Learning Models (LLMs) to ensure fast and accurate data access. Integrating a semantic layer with LLMs offers a clean solution, especially for AI chatbots, enabling businesses to generate quick responses and reports based on their data. This combination is advancing business intelligence and making it easier for people to interact with data.
Learn more in this recorded webinar, where Fleet Management company Quantatec discusses the AI Bot they developed on top of the Cube semantic layer to enable non-technical employees to easily access data without writing SQL queries or building their own dashboards.
Effective Role of Semantic Layer in AI Chatbots and Data Accuracy
AI chatbots, powered by Language Learning Models (LLMs), can understand and respond to complex queries in natural language with high accuracy. This makes data analysis more accessible to non-technical users and speeds up the process of data retrieval and analysis. However, the challenge lies in ensuring the chatbot interprets and responds to user queries accurately, which is where the semantic layer comes in.
The semantic layer acts as an intermediary between the AI chatbot and the database, ensuring that queries are correctly executed and controlling access to sensitive data to enhance security. Additionally, the semantic layer improves performance by pre-computing complex joins and calculations, leading to faster data analysis and a better user experience.
In summary, the fusion of a semantic layer with an LLM for AI chatbots is modernizing business intelligence and embedded analytics data application. It enhances data analysis efficiency, precision, and security while streamlining access to data analysis. Learn more in this recorded webinar where Fleet Management company Quantatec discusses the AI Bot they developed on top of the Cube semantic layer for easy data access by non-technical employees.