GenAI has the potential to lower the threshold for non technical users to engage in data analytics. According to a study performed by Lucidworks with medium to large companies 75% of senior leaders believe the main use case of GenAI is data analytics. Instead of having to learn complex syntax, end users can ask the GenAI agent for insights using natural language. The Agent then searches for the relevant data in your company’s body of knowledge using Retrieval Augmented Generation (RAG) to formulate an answer. This creates new privacy and security challenges, which is being echoed by industry leaders. A study by Gartner highlights that 30% of enterprises using GenAI have experienced a security breach.
Raito manages and monitors the data access of Retrieval Augment Generation (RAG) across structured and unstructured data used by GenAI Agents, and user access to prevent unauthorised access, accidental disclosure, and data poisoning. By employing access-as-code (YAML) and a seamless integration with your CI/CD pipeline, Raito empowers data teams to shift data security left. This shift places security early in the data stream and places responsibility in the hands of the data owners who thoroughly understand the data and can use Raito’s intuitive user interface and user experience.
