When introducing AI, have your Standard Operating Procedure (SOP) manuals been prepared?
Many companies skip a crucial step when introducing AI: preparing material for AI to 'learn'.
No matter how strong the language model is, it cannot "understand your process" by itself. It needs references, context, clear format Standard Operating Procedures (SOP) and knowledge content.
This article will guide you through: how companies should prepare documentation materials before AI implementation to be understandable, searchable, referenceable, and generatable.
Learning Materials ≠ Data: What AI Needs is 'A Format It Can Learn From'
Companies do not lack data, but most of it lacks 'meaningfulness'. Common issues include:
- SOPs are all written in PDFs and cannot be segmented
- The document structure is chaotic with no hierarchical titles
- The process only has charts without explanatory texts
- Some are in ERP, others in Google Drive, etc.
This content may make sense to humans but it's noise for AI.
What kind of document structure suits AI?
The following formats and strategies should be considered when building AI-learnable content:
- Has a hierarchical title system: letting AI identify paragraph topics (H1→H2→H3)
- Segment rules: each segment should control around 100~300 words with a single semantic focus
- Process in descriptive sentences: filling process diagrams with narrative sentences, such as 'each order requires dual approval'
- Keyword marking: like 'exception handling', 'attention matters', 'related regulations'
- Add metadata: for example, 'department: customer service', 'version: 2024/03'
These structures not only help AI to retrieve and generate content but also improve the quality of internal knowledge files.
Common preparation directions: Transforming messy data into semantic databases
- Inventory content: Which processes have SOPs? Where are they located? Are the versions correct?
- Structuralization process: transitioning from essay-style to modular paragraphs
- Supplementing descriptions: do flowcharts and pictures have enough textual explanations?
- Format conversion: consolidating Word, PDF into readable formats (like JSON, Markdown)
- Vector database importation: establishing semantic search and content correlation abilities
NT Tech's starting point: Preparing AI-readable content instead of just writing AI
NT Tech understands that proper document preparation is the key to successful AI implementation. We assist companies in:
- Inventory, convert and strengthen SOP files
- Creating templates for AI-readable process semantics
- Designing retrieval strategies for documents and generation response processes
- Integrating vector databases with private model deployment
More data does not mean better. The goal is to make the data usable by AI effectively. We help you build a bridge from 'documents' to 'knowledge'.
