Enrichment Techniques

To build a robust knowledge graph, Project Zero employs advanced enrichment techniques, including artificial intelligence (AI), natural language processing (NLP), and classification models. AI-driven NLP enables the system to extract insights from unstructured data, such as protocol documentation or social media activity, and align these with on-chain events. This creates a bridge between blockchain activity and external contexts, offering a holistic view of ecosystem dynamics.

A key advancement is the use of AI to generate Block Functions code directly from NLP inputs. Users can describe their data transformation needs in natural language, and AI translates these descriptions into executable JavaScript code. These AI-generated Block Functions can then be deployed for real-time data streaming, enabling AI Agents to consume customized, enriched blockchain insights instantly.

Additionally, advanced classification models further enrich the data by categorizing transactions, flagging anomalies, and identifying protocol-specific behaviors. For example, a transaction involving multiple tokens and smart contracts might be tagged as a DeFi yield farming operation, providing agents with actionable context. These enrichment techniques ensure that the knowledge graph is not just a database but an intelligent insights layer, seamlessly integrating AI-driven customization and real-time streaming.