LLM Capability

Converting unstructured content stored in S3 (documents, images, logs) into vector representations for similarity search.

Querying S3-derived vector embeddings to find content by meaning rather than exact keyword match.

Using LLMs to extract structured metadata (entities, categories, summaries, key-value pairs) from unstructured objects stored in S3.

Using LLMs to infer or suggest schemas from semi-structured data (JSON, CSV, nested formats) stored in S3.

Using LLMs to categorize, tag, or label S3-stored objects based on content analysis — by topic, sensitivity level, or compliance category.

Using LLMs to translate natural language questions into executable queries (SQL, API calls) over S3-backed datasets.