Blog: Vector Databases

For VC teams, valuable knowledge is everywhere: PDFs, inboxes, call transcripts, news feeds, and internal notes. The problem is getting the right context when you actually need it. We built a platform that brings all of this information into a single searchable knowledge base, with LLM agents on top that can: • prepare meeting briefings • research people and companies • answer questions across the firm’s internal knowledge • continuously ingest and structure new information In the article, we go under the hood and explain how the system works, including its storage architecture, seven-stage ingestion pipeline, Airflow automations, and the agent layer that we substantially redesigned after the first production release. We also cover a production incident that changed how we approached monitoring and reliability. If you’re building RAG systems, internal AI assistants, or agentic workflows on top of large amounts of unstructured company data, this one gets pretty technical.