Make LLMs understand your private company data.
RAG Application Developer (Retrieval-Augmented Generation)
Build "Chat with your Data" applications. I build RAG pipelines using Pinecone, pgvector, and LangChain.
RAGVector DBpgvectorSemantic Search
Core Capabilities
Document Parsing (PDF/Docx)
Embedding Generation
Vector Search
Context Injection
Related Case Studies
Frequently Asked Questions
What is a RAG application?
RAG allows an AI to search your private documents (like company policies or past tickets) and use that specific information to answer user questions accurately.
Which vector database is best for RAG?
For Postgres-heavy apps, I use `pgvector` to keep relational and vector data together. For massive scale, I use Pinecone.