Translating NAICS to NACE in One API Call

TL;DR: Use the /translations endpoint to convert any NAICS code to NACE (or any other system) instantly. This post walks through single lookups, batch translation, handling one-to-many mappings, and finding gaps.

The setup

System	Region	Codes	Structure
NAICS 2022	North America	2,125	2-6 digit numeric
NACE Rev 2	European Union	996	Letter + 2-4 digit

Both classify economic activities. Both have hierarchical structures. But they slice industries differently and use incompatible code formats.

Single translation

curl "https://wot.aixcelerator.ai/api/v1/systems/naics_2022/nodes/5415/translations"

{
  "naics_2022": "5415",
  "isic_rev4": "6201",
  "nace_rev2": "62.01",
  "sic_1987": "7371",
  "anzsic_2006": "7000",
  "nic_2008": "6201"
}

NAICS 5415 (Computer Systems Design) maps to NACE 62.01 (Computer programming activities). One call, no lookup tables.

Batch translation

import requests

NAICS_CODES = ["5415", "4841", "6211", "2362", "3121"]
BASE = "https://wot.aixcelerator.ai/api/v1"

for code in NAICS_CODES:
    resp = requests.get(f"{BASE}/systems/naics_2022/nodes/{code}/translations")
    data = resp.json()
    nace = data.get("nace_rev2", "no mapping")
    print(f"NAICS {code} -> NACE {nace}")

Output:

NAICS	Description	NACE
5415	Computer Systems Design	62.01
4841	General Freight Trucking	49.41
6211	Offices of Physicians	86.21
2362	Nonresidential Building Construction	41.20
3121	Beverage Manufacturing	11.01

The translation flow

sequenceDiagram
    participant Client
    participant API as WorldOfTaxonomy API
    participant DB as PostgreSQL

    Client->>API: GET /systems/naics_2022/nodes/5415/translations
    API->>DB: Query equivalence table (both directions)
    DB-->>API: All crosswalk edges for NAICS 5415
    API-->>Client: JSON with all equivalent codes by system

Handling one-to-many mappings

Not all translations are 1:1. Use the equivalences endpoint for the full picture:

curl "https://wot.aixcelerator.ai/api/v1/systems/naics_2022/nodes/5415/equivalences"

Each edge includes a match type:

Match type	Meaning	When it happens
`exact`	1:1 correspondence	Derived systems (WZ = NACE)
`broad`	Source is broader than target	ISIC division -> multiple NAICS groups
`narrow`	Source is narrower than target	Detailed NAICS -> broad ISIC
`partial`	Overlapping but not contained	Different structural cuts

Finding gaps

# NAICS codes with no NACE equivalent
curl "https://wot.aixcelerator.ai/api/v1/diff?a=naics_2022&b=nace_rev2"

This returns the exact codes you need to map manually - the gap analysis that usually takes days of spreadsheet work.

Beyond NAICS and NACE

The same pattern works for any system pair in the graph:

HS trade codes to UNSPSC product codes
SOC occupation codes to ESCO skills
ICD-10-CM diagnoses to ICD-11
Any of the 1,000 systems to any other

If a crosswalk edge exists, the translation works. If it does not, the diff endpoint tells you exactly what is missing.