📄️ Agents
Our product is very simple, it can be divided into two fundamental features: managing your AI agents and chatting with them. An Agent within the Denzing application is an entity that serves as a specialized expert in interacting with complex data. Users can send data-related queries to an Agent, and the Agent can retrieve, analyze, and respond based on its expertise in the data source it is bound to. Each Agent is connected to a specific data source (e.g., a database, CSV file, etc.), and it can help users interact with the data in a conversational manner.
📄️ Data Sources
Denzing empowers users to connect with their data—wherever it lives. Whether your files are stored in the cloud or locally, our platform supports seamless integration with a wide variety of data sources, enabling Agents to interact with your data in real time through natural, conversational queries.
📄️ Metadata
Metadata provides critical context and structure to data, enabling efficient querying and accurate responses. It is categorized into two types: Schema Metadata and Semantic Metadata. This documentation details these metadata types, along with examples in YAML format.