SurfaceDocs + LlamaIndex: From RAG Pipeline to Shareable Report

SurfaceDocs + LlamaIndex: From RAG Pipeline to Shareable Report Your RAG pipeline answers questions beautifully. It retrieves the right chunks, synthesizes a coherent response, even cites its sources. Then the output prints to stdout and dies. What if every answer your pipeline produced was instantly a shareable, hosted document? The last mile problem RAG pipelines are the backbone of most production LLM applications. You invest real engineering effort into chunking strategies, embedding models, retrieval tuning, prompt design. The analysis is the hard part, and we've gotten good at it. But sharing the result? That's where things fall apart. You copy-paste into a Google Doc. You screenshot a notebook cell. You build a bespoke Flask app to render responses. You email a JSON blob and hope someone reads it. Every team reinvents this output layer, and it's never the part anyone wants to work on. The pipeline deserves a better destination than print(response) . The minimal version: query an