DATA CAPABILITY
Vector and retrieval architecture for grounded enterprise AI
Inference Stack helps enterprises choose and implement the right retrieval substrate for grounded AI systems. We work across managed vector platforms and in-database vector architectures to support retrieval quality, metadata filtering, operational simplicity, and long-term maintainability.
Retrieval infrastructure we work with
Pinecone
PostgreSQL + pgvector
Hybrid retrieval patterns
Metadata modeling
Reranking and evaluation
Retrieval operations and tuning
How we approach retrieval architecture
The right retrieval architecture depends on scale, tenancy, latency, metadata filtering, governance requirements, and operational constraints. We help organizations make these choices deliberately rather than defaulting to the first vector database that appeared in a tutorial.
Need a retrieval architecture that will hold up in production?
Inference Stack helps enterprises design the vector and retrieval substrates required for grounded, governable AI systems.