AI business assistant · Workflow
Create a structured product list with AI
Turn notes, files or product facts into a structured product list with consistent fields, review checks and an export-ready business file.

Short answer
ValueSpace can turn product notes, source files or pasted facts into a structured list with agreed columns such as name, SKU, category, price and status. This workflow produces a working table or file, not a designed visual catalogue, and every missing or conflicting value should remain visible for human review.
Define the product list before filling it
Choose the purpose, required columns, units, currency, allowed categories and identifier rules. A stock upload, purchasing list and sales reference may need different fields even when they use the same products.
Organise source facts row by row
The assistant reads the supplied notes or files, normalises repeated wording and creates one row per agreed item. It can flag duplicates, inconsistent units and empty values without silently filling them.
- Keep source wording or references available for reconciliation.
- Separate confirmed values from suggestions and missing information.
- Check identifiers, prices, tax fields, units and variants before reuse.
Review the list before import or publication
Reading source files and checking existing values is read-only. Structuring rows, suggesting duplicates and preparing validation results can happen automatically inside the task. Importing the list, overwriting product records, changing prices or publishing product content requires explicit approval and a compatible connected system.
ValueSpace
Business work, clearly controlled
Prerequisites and limitations
The business must define the canonical fields and supply trustworthy source data. ValueSpace does not verify ownership, regulatory claims, stock accuracy or prices that are absent from the sources, and a structured product list is not a designed visual catalogue.
How this works in ValueSpace
ValueSpace supports the workflow described in “Create a structured product list with AI” within the available data, connection and permissions. The visible result and approval boundary remain part of the same reviewable task.
- Choose the purpose, required columns, units, currency, allowed categories and identifier rules. A stock upload, purchasing list and sales reference may need different fields even when they use the same products.
- The assistant reads the supplied notes or files, normalises repeated wording and creates one row per agreed item. It can flag duplicates, inconsistent units and empty values without silently filling them.
- Reading source files and checking existing values is read-only. Structuring rows, suggesting duplicates and preparing validation results can happen automatically inside the task. Importing the list, overwriting product records, changing prices or publishing product content requires explicit approval and a compatible connected system.
- The business must define the canonical fields and supply trustworthy source data. ValueSpace does not verify ownership, regulatory claims, stock accuracy or prices that are absent from the sources, and a structured product list is not a designed visual catalogue.
- A safe sample of product notes, a spreadsheet or another current source.
- The required columns, units, currency and category rules.
- Examples of duplicate, variant and missing-value handling.
Continue with Find supplier contact details with AI and public sources.
Frequently asked questions
ValueSpace can turn product notes, source files or pasted facts into a structured list with agreed columns such as name, SKU, category, price and status. This workflow produces a working table or file, not a designed visual catalogue, and every missing or conflicting value should remain visible for human review.
What to prepare for a practical test
Use a safe real example, define who may approve the result and remove personal or confidential data from the working material.
- A safe sample of product notes, a spreadsheet or another current source.
- The required columns, units, currency and category rules.
- Examples of duplicate, variant and missing-value handling.
- The target file format and approver for any later import.


