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Saudi Arabic Customer Support

50,000 customer-service conversations across four Saudi dialects and four sectors.

50,000
rows
6
dimensions
4
formats
22
checks

Overview

The flagship dataset. Fintech, telecom, delivery and e-government support conversations written in Najdi, Hejazi, Sharqiyah and general Saudi registers — with per-row metadata for dialect, sector, sentiment and topic, and outcomes that are not all happy endings.

conversations
50,000
dialects
4
sectors
4
brands
18
format
JSONL
license
commercial

Row specimen

jsonl
{
  "id":           "uuid",
  "status":       "completed",
  "metadata":     { "dialect": "Najdi", "sector": "Fintech", "sentiment": "Angry", "topic": "Transfer Failed" },
  "conversation": [ { "role": "user", "content": "..." }, { "role": "agent", "content": "..." } ],
  "slug":         "transfer-failed-a1b2c3"
}

Field schema

Fields as they appear in every row of the file.

idstringStable row identifier
metadataobjectDialect, sector, sentiment and topic
conversationarrayThe turns, user and agent alternating
slugstringURL-safe name derived from the topic

Inspection report

22 / 22
✓Turn count bounds✓Role alternation✓Minimum turn length✓No adjacent duplicates✓Every turn has content✓Levantine contamination✓Robotic support phrasing✓English inside dialogue✓Caricatured dialect✓Injected amount present✓Reference number present✓Brand named by agent✓Agent introduces itself✓Agent name not pre-known✓Sector vocabulary✓Sector-fit resolution✓Dialect hospitality marker✓Forbidden dialect slang✓Brand capability match✓Verification before resolution✓Dialect marker frequency✓Hospitality phrase repetition

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