Organizational knowledge systems
Knowledge Capture & Operational Documentation
A system that turns tacit operational knowledge into structured documentation, keeps it current, and makes it accessible through a grounded internal assistant.
Conversation-to-SOP workflow
Incremental documentation indexing
Searchable assistant grounded in internal sources
The most valuable knowledge in an organization is often the least accessible. It lives in the heads of experienced operators, in one-off conversations, and in scattered documents that newcomers do not know to search for.
I built this system to turn that tacit knowledge into an operating asset: something teams can capture, standardize, maintain, and use when they need an answer.
From Expert Conversation to Usable Documentation
The workflow begins with a conversational assistant that interviews an operator about how their work actually gets done. Instead of asking someone to start with a blank document, it guides the conversation and preserves the full exchange in a shared workspace.
An AI documentation pipeline then turns sufficiently detailed conversations into structured process documents. It follows a standard format, creates supporting diagrams where useful, and publishes the result into the organization’s documentation library. This makes the output usable as an SOP—not merely a transcript or a collection of notes.
Keep the Knowledge Base Alive
Documentation is only useful if it can stay current. The indexing layer detects new and changed documents, updates only what needs to be reprocessed, and makes the documentation semantically searchable. That avoids the common failure mode of treating a knowledge base as a one-time migration project.
The internal assistant retrieves relevant documentation before answering a question, giving employees a direct path from “How does this work?” to an answer grounded in the organization’s own processes and source material.
Why This Matters
This is not just a chatbot. It is a way to reduce dependence on tribal knowledge, accelerate onboarding, and give teams a more reliable way to preserve and reuse operational judgment. The work combines human-centered knowledge capture with the data and retrieval systems needed to make that knowledge useful at scale.
Tech Stack
Python, Streamlit, Claude, OpenAI embeddings, vector search, Google Drive and Google Docs APIs, structured documentation generation, and semantic retrieval.