Flux Labs
Enterprise KnowledgeBase
- Category
- RAG & Search
- Year
- 2025
- Client
- Flux Labs
The challenge
Flux's engineering and operations teams had documentation scattered across Notion, Confluence, internal Slack threads, and legacy PDFs. Search was keyword-only and routinely returned stale or irrelevant pages.
What we built
We built an ingestion pipeline that continuously syncs from all their source systems, chunks and embeds documents, and surfaces results through a semantic search interface. Answers are grounded with inline citations so engineers can verify sources. The interface also supports follow-up questions within a session, turning one-off searches into genuine knowledge conversations.
Impact
5×
Faster time-to-answer vs. keyword search
12k+
Documents indexed across 4 source systems
91%
Query satisfaction rate in internal survey
Zero
Hallucinated answers (all grounded in sources)
Next project
Document Intelligence Platform
Meridian AI
