Aspected Database

Unified retrieval for RAG systems

Most RAG systems don’t fail at generation, they fail at retrieval. Today’s approach is fragmented:

• Vector search handles meaning
• Metadata is applied as filters
• Rerankers try to fix the gaps

This leads to complex pipelines and unreliable results.

Aspected Database replaces this with a single, unified model.

Aspected Database encodes semantics and metadata together into a single vector.

Instead of:
• Embedding + filters + reranking

You get:
• Multi-dimensional retrieval in one step

Comparison

Traditional systems ask:
“Does this document match the filter?”

Aspected Database asks:
“How much should this matter for relevance?”

This enables:
• Weighted ranking instead of hard constraints
• Context-aware retrieval
• More natural and accurate results

Comparison

Nothing else matters

More in dept information about the Aspected Database, the technology and idea behind it and its place in the full Aspected stack.

WhitepaperApril 2026

WhitepaperApril 2026