Smart Meter Trade Knowledge Base

Overview

The source material spans product documents, certification files, technical support records, product images and customer-history files.

The goal is a trustworthy internal knowledge layer, not a public document dump.

Problem

Large folders accumulate duplicates, conflicting versions and unclear ownership.

Sensitive customer material must remain separate from content that can safely support public writing or sales work.

Approach

Inventory first, then classify by product, document type, market, lifecycle and sensitivity.

Treat deduplication, naming and permissions as prerequisites for retrieval.

Design answers to carry source references so uncertainty remains visible.

What AI Did

AI can assist with classification proposals, duplicate candidates, summaries and retrieval experiments.

It does not decide access rights or silently replace the source record.

Challenges

File names and folder locations do not always reflect document meaning or freshness.

Visual files and scanned technical documents need different processing from ordinary text files.

Result

The knowledge-base design is in progress. The approximately 9.7 GB source volume is the only published scale figure; no retrieval-accuracy claim is made.

Lessons Learned

Retrieval quality depends on document hygiene, provenance and permissions before it depends on model choice.

A smaller verified corpus can be more useful than a larger ungoverned one.