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Used to represent text for semantic retrieval and related-content matching.
Used to represent text for semantic retrieval and related-content matching.
Content embeddings for Alex OS's semantic search.
Content embeddings for Alex OS's semantic search.
Embeddings power the semantic search in Alex OS, turning text into vectors that retrieve contextually relevant content rather than just keyword matches.
Embeddings
Used to represent text as dense vectors for semantic retrieval and related-content matching. Currently active in production work, with practical confidence built through direct application.
Where it's applied
Content embeddings are the retrieval backbone of Alex OS — the FastAPI layer that serves grounded, journey-aware answers from the CMS. Without embeddings, that system falls back to brittle keyword lookup.
Skill snapshot
Experience level: working knowledge. Active: yes. Evidenced in the Alex OS project, which also connects to Alex's broader work in RAG and Knowledge Retrieval — a pattern where embeddings sit at the core of the retrieval pipeline.