Part 9/13:

• Content Summarization: Providing condensed versions of lengthy documents.

• Embedding Storage: Using vector databases such as Pinecone or PG vector for efficient similarity searches.

An essential aspect is ensuring that each embedding carries tags—like URLs or asset identifiers—to improve explainability and facilitate data provenance.

The Necessity of Knowledge Graphs and Contextual Relationships

While vector embeddings and metadata enrich the data, they may not fully capture business perspectives or process-oriented context. Here, knowledge graphs step in to map organizational entities, workflows, and relationships systematically.

For example:

• Linking marketing campaigns to dashboards and KPIs.