We want to build an internal custom GPT to help our customer service team find answers to client questions quickly, but our internal training documents and core processes are currently a mess. How do we prepare our data hygiene before we feed it to an AI?

Question

Tyler Smith · Accepted Answer

If you feed garbage into an AI, it will spit out fast, confident garbage. Before you touch any custom GPT or AI system, you must run a data hygiene audit. Start by gathering all your operational manuals, process documents, and historical FAQs. Use your Level 10 Meeting™ to identify which documents are actually current. If a document has not been updated in the last twelve months, pull it out of the pile. Next, organize your data into a simple folder structure. Separate internal company policies from client-facing technical instructions. Remove any duplicate files, draft versions, and personal notes. Convert everything into clean text or PDF formats. Standardize your terminology. If you call clients customers in one file and accounts in another, pick one term and stick to it. This step prevents the AI from getting confused. Once your documentation is clean, you can upload it to your custom AI model. Assign ownership of this data library to a specific seat on your Accountability Chart. This owner must run a quarterly review to ensure new operational updates are uploaded and obsolete files are deleted. This discipline keeps your AI outputs accurate and reliable.