Decode manufacturer part codes into catalog attributes
Turn encoded component names into explicit technical fields using manufacturer documentation. Validate decoding rules before applying them to a product catalog.
How this works
A manufacturer part number can encode dimensions, material, packaging or an electrical characteristic. The code is meaningful only within the correct family and document version. Guessing from similar products can create precise-looking but false catalog specifications.
Use AI to help extract an explicit decoding grammar from approved documentation. Apply the resulting rules deterministically and test them against expert-labeled examples. The output records which values were decoded, which were supplied directly and which remain unknown.
Before you start
Family-specific documentation
Obtain the manufacturer’s applicable naming legend, tables and revision information.
Domain reviewer
Name the product-data specialist who can verify units, exceptions and family membership.
Independent examples
Reserve known examples for validation, including invalid and unusual codes rather than only common products.
Prepare the inputs
- part_numbers
- Required
stable row IDs and exact strings
Preserve leading zeros, separators, suffixes and letter case until their meaning is established.
- legends
- Required
documents, pages and applicable families
Require version and family coverage; flag incomplete tables or references.
- target_schema
- Required
attribute names, types and units
Define whether a field is mandatory, optional or not applicable.
- reference_examples
- Required
code and expert-confirmed fields
Keep validation examples separate from examples used to draft rules.
Implementation, step by step
Partition the product families
- Group codes only where a supplied reference establishes the same encoding scheme.
- Keep ambiguous family membership in a review set; a shared prefix is a clue, not sufficient proof.
Checkpoint: Every supported row points to an applicable family and document version.
Write explicit decoding rules
- Extract token positions, allowed values, lookup tables and conditional suffix meanings.
- Link each rule to its source page and preserve exceptions, including fields that are absent rather than zero.
Checkpoint: A reviewer can explain each target attribute without relying on model intuition.
Implement a bounded decoder
- Represent rules as a lookup table, formula or small parser with explicit unsupported-code outcomes.
- Keep parsing separate from catalog writes; if code is generated, inspect and run it in a local test environment with no network or mutation requirements.
Checkpoint: The decoder produces typed values and a rule identifier for every result.
Test known and adversarial examples
- Run independent labeled examples plus truncated codes, unknown suffixes, wrong families and repeated separators.
- Compare field-level results, including missing values and units. Record failures by rule rather than hiding them in one overall score.
Checkpoint: Unsupported inputs fail visibly and known examples match approved expectations.
Process the catalog snapshot
- Apply only approved rules to the supplied snapshot and preserve source row IDs.
- Flag conflicts with existing catalog attributes for review; do not overwrite a current value merely because the new rule produced another value.
Checkpoint: Each row has decoded values, evidence and a status.
Review exceptions and package the import
- Resolve disputed rules with the specialist and rerun affected examples after changes.
- Export a proposed import and an exception queue with the rule version; keep the original catalog snapshot available for comparison.
Checkpoint: The receiving team can identify exactly which fields would change and why.
Decisions along the way
A code is syntactically valid but absent from the legend
Return unsupported rather than extrapolating a new suffix meaning.
Two document revisions decode the same token differently
Require a revision match or hold the row.
A derived value conflicts with a measured specification
Preserve both and ask the domain owner which source governs.
What you will produce
decoded-attributes.csv
CSVLong-form attributes ready for review before import.
Include: source_row · part_number · family · attribute · value · unit · rule_id · document_version · status
decoder-evaluation.csv
CSVA field-level validation record including rejection tests.
Include: example_id · field · expected · actual · result · rule_id
Check the result
- Check units and leading-zero preservation on every new family.
- Verify unknown tokens never receive invented meanings.
- Re-run all affected examples after a rule change.
When something goes wrong
A table is unreadable
Request a clearer reference and hold its dependent attributes.
Unexpected code frequency increases
Pause that family and investigate whether a new naming revision was introduced.
A worked example
SYNTHETIC EXAMPLE · NOT A REPORTED BUSINESS RESULT
Request
Synthetic: decode a documented seal family.
Inputs
The supplied legend defines S-DD-M, where DD is diameter in millimeters and M is E for EPDM or N for nitrile. Rows are S-20-E and S-20-X.
Expected result
The first row yields 20 mm and EPDM with its rule reference. The second retains 20 mm only if partial decoding is permitted, and holds material as unknown; X is never guessed from nearby items.
Run a small pilot
Start small
One documented family with independently labeled common and edge cases.
Record the baseline
Measure manual attribute-entry time and field errors on the same snapshot.
Agree success criteria
Agree per-field accuracy and unsupported-input handling requirements before catalog import.
Stop or revise
Stop when source revisions, family membership or critical units are uncertain.
Keep the scope clear
- Decoded attributes do not establish product interchangeability or suitability for a safety-critical use.
- Catalog publication and master-data changes require their own authorized handoff.
Check before using
A product-data specialist approves decoding rules and checks unsupported or conflicting codes.
Business activities
- Manage product catalogs and storefronts
- Plan inventory and production
FROM A RECIPE TO YOUR WORKFLOW
Bring the company context together.
This workflow needs reliable inputs before it needs a better prompt. Moat8 Vault brings working information into a readable archive for the AI tools you use.
For this recipe: Part-number list · Manufacturer encoding legends · Expert-labeled examples
Start with one recurring task, agree which sources to use, and review the first result with your team.
Discuss this workflow