Case Study
Semantic Retrieval Platform
A search layer combining embeddings, query rewriting, and taxonomy constraints for high-signal discovery.
Challenge
Keyword-only lookup struggled with domain vocabulary and intent mismatch across internal knowledge bases.
Approach
Used pgVector with OpenAI embeddings plus taxonomy-aware post filters for accurate top-K retrieval.
Period
2024 - 2025
PostgreSQLpgVectorOpenAIJavaSystem Design
Outcomes
- Improved knowledge discovery efficiency by 40%.
- Made search quality more stable for ambiguous and long-form queries.
- Created a strong foundation for AI-assisted support workflows.