Engineering of Retrieval-Augmented Generation (RAG) architectures for processing proprietary business data. I implement vector databases (FAISS) and semantic search pipelines to facilitate accurate information retrieval for LLMs. This service includes the development of asynchronous backends to manage state across complex, multi-turn interactions and ensuring data consistency within the retrieval process.

Deliverables: FastAPI-based backend, integrated vector database, and custom retrieval logic optimized for low latency and high accuracy.

The listed price represents a baseline for standard requirements. Final pricing is mutually agreed upon after a technical review of the project's scale, scope and urgency.