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General-purpose LLMs like ChatGPT are excellent at writing prose, but they generate numbers — which makes them unreliable for tourism figures that need to be defended. DataGreat inverts the architecture: deterministic rules compute every number from verified WTTC + macro data, and the AI only writes the prose around those locked values.
The practical consequence is trust. With an LLM, the same prompt can produce different figures on different runs, and citations are often invented. With DataGreat, the same inputs always produce the same report, and every claim carries a page-anchored WTTC citation.
| Dimension | ChatGPT | DataGreat |
|---|---|---|
| Who produces the numbers | The model (generated) | Deterministic rules over WTTC data |
| Hallucination risk | High — every figure a guess | Zero — narrator locked to a claim ledger |
| Citations | Often invented | WTTC EIR 2025 page anchors |
| Reproducibility | Low — prompts drift | 100% — same inputs, same report |
| Verified coverage | Everything, none verified | 42 WTTC-verified markets |
| Structured output | Freeform text | Tables, charts, provenance pills |
| Prose quality | Strong | Strong — Claude writes the narrative |
| Best used for | Drafting, ideation | Defensible, sourced tourism reports |
Use ChatGPT to draft and ideate. Use DataGreat when the tourism numbers have to be correct, cited, and the same every time you run them.
You can ask, but a general LLM generates figures — they may be wrong, and they can change between runs. DataGreat computes every tourism number deterministically from verified WTTC data and anchors each one to its source, so the figures are defensible and reproducible.
Yes, but only for the prose layer. The numbers are computed by deterministic server-side rules over WTTC + macro datasets; the AI narrator is forbidden from emitting any figure not present in the data, and a post-validator nullifies any that slip through.
Yes. Re-running the same inputs in DataGreat produces the same report every time. A general LLM's output drifts with prompt phrasing and model updates, which is why its numbers can't be relied on for investment-grade work.
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Generate a verified, WTTC-anchored report in ~30 seconds.