Knowledge Center

Users can inject their knowledge into the platform through various means, such as uploading documents, providing URLs, connecting to databases, or direct conversation. The platform processes this information through domain-specific workflows, converting it into semantic, structured domain knowledge.

The Knowledge Center includes two types of data:

• Knowledge: Unstructured data such as documents and URLs

• Database(Coming Soon): Structured data from uploaded Excel files or connected databases

Why we need a Knowledge Center:

• To Ground AI in Reality: Without a knowledge base, an AI model (the agent's brain) relies solely on its internal, memorized training data. This data can be outdated or incomplete, leading to "hallucinations" or made-up answers. A knowledge base provides a factual source of truth.

• To Ensure Currency and Relevance: The world is constantly changing. You can update a knowledge base with new information (e.g., new company policies, recent news, product updates) instantly, without the massive cost and time of retraining the entire AI model.

• To Provide Domain-Specific Expertise: You can create specialized knowledge bases for specific fields like medicine, law, or engineering, giving an AI system expert-level information in that domain.