Everything, answered.

DataGreat is a tourism intelligence platform. It turns the WTTC Economic Impact Research 2025 dataset — 42 countries, 26,880 verified metric rows and 11,647 rankings — into investor-grade reports that generate in roughly 30 seconds. Every quantitative claim in every report traces back to its exact WTTC source page, so analysts get consulting-grade rigor at a subscription price.

The narrator (Claude) never invents numbers. It is locked to a claim ledger: only values that exist in our verified WTTC tables can appear in the prose. Every quantitative claim ships with a provenance pill linking to the exact source page. A server-side post-validator nullifies any figure that is not in the ledger, so a fabricated number cannot reach the reader.

The tourism catalogue is anchored to the WTTC Economic Impact Research 2025 (EIR 2025), published in April 2025. Macro indicators are cross-referenced against IMF and World Bank releases. Each country page cites the specific WTTC publication, document title and PDF page it draws from, plus the date the figure was last accessed.

WTTC EIR refreshes annually (Q2 each year) and DataGreat tracks the latest release. Macro indicators from the IMF and World Bank refresh quarterly. Derived comparisons — such as Risk Radar severity bands — re-run weekly, so peer rankings can move even when the underlying WTTC figure is unchanged. Every page shows the date its data was last reviewed.

Yes. The same inputs always produce the same report — figures are computed by deterministic rules, not sampled from a model. That makes side-by-side comparisons honest, peer review trustworthy, and automation via the API safe. Only the surrounding prose is model-written, and it is constrained to the numbers already computed.

DataGreat is a product of Solustiq Software & AI Technologies Inc., founded in 2023, with offices in Edirne (Turkey) and Dubai (UAE). Research methodology is led by Alper Tekin, drawing on a decade of tourism-industry leadership at Safaryar Holidays, a data-driven DMC. The platform pivoted to a tourism-first focus in 2026 around the WTTC dataset.

All 42 economies in the WTTC EIR 2025 release — including Türkiye, Spain, France, Italy, Germany, the United States, the United Kingdom, the UAE, Saudi Arabia, Greece, Egypt, Morocco, Mexico, Thailand, Indonesia, Japan and China. The free Explore tier includes 5 reference countries (TUR, USA, GBR, FRA, ESP) so you can evaluate output before subscribing.

Country datasets carry a 2019 baseline, 2024 actuals and 2025 forecasts, with GDP-share projections extending to 2034/2035. This lets you measure pandemic recovery against 2019, read the current state from 2024, and model demand a decade out — all from one verified source rather than stitched-together estimates.

There are 24 verified tourism modules — Country Snapshot, TAM·SAM·SOM, Demand Forecast 2024–2034, Pandemic Recovery, Source Markets Inbound, Investment Attractiveness Score, Regional Benchmark and more — plus 8 curated presets that bundle modules for common use-cases. A separate set of 38 general-research beta modules is clearly marked as LLM-generated and kept out of the verified catalogue.

A preset is a named bundle of modules for a common job. For example, the 'Investor Pitch' preset runs TAM·SAM·SOM, a 10-year demand forecast, pandemic recovery and global rankings in a single pass, so you get a complete deck-ready analysis without picking modules one by one. There are 8 presets spanning investment, policy and benchmarking work.

Yes. Side-by-side benchmarking scales with your plan: 10 countries on Analyst, 30 on Agency and all 42 on Institute. Benchmarks rank markets on GDP contribution, employment share, arrivals, spend-per-visitor and investment momentum, each figure anchored to the same WTTC release so the comparison is apples-to-apples.

DataGreat also offers general-purpose AI research modules — competitor analysis, buyer persona, SWOT, pricing strategy — flagged as optional beta. These are LLM-generated and may contain unverified figures, so they are kept visually and structurally separate from the WTTC-anchored tourism catalogue. Use them for ideation, not for investment or policy decisions.

In end-to-end tests, a Türkiye report with 30 verified claims and inline citation chips finished in about 30 seconds. The pipeline runs four stages — profile load, module computation, narrator prose, finalisation — and you watch it happen live rather than waiting on a black box.

Yes. PDF export is available from the Researcher tier upward. Analyst and Agency tiers add white-label or full-brand PDFs and shareable public report links that need no login for the viewer. Shared links expire after 30 days on Analyst. API access for programmatic export ships with Agency and Institute.

Categories with insufficient data return an `insufficient_data` badge instead of a fabricated answer. Confidence scores drop accordingly and the affected section is flagged, so reviewers can see exactly where coverage runs out. A handful of countries are atlas-baseline entries whose full WTTC factsheet is still pending — these are published but clearly marked.

No. Every numeric field in personas, campaign briefs and risk reports is computed from WTTC plus macro data via deterministic rules. The model's only job is writing prose around those numbers. It is explicitly forbidden from emitting figures not present in the data block, and a server-side validator nullifies any that slip through.

Risk Radar re-runs every Monday at 04:00 UTC. Even when underlying WTTC figures haven't changed, peer comparisons can shift a market between severity bands, so the weekly cadence keeps the signal current. Agency and Institute tiers can receive changes via webhook or email digest rather than checking manually.

ChatGPT generates the numbers; DataGreat does not. Our pipeline runs deterministic rules over verified WTTC plus IMF/World Bank data, computes severities and shares server-side, and only hands the prose layer to the model. Every claim links to a citable source, and re-running the same inputs produces the same output — which a general chatbot cannot guarantee.

The narration layer uses Anthropic's Claude models. Crucially, the model receives a pre-computed data block and is constrained to it — it phrases and structures the analysis but never sources the figures. This split (deterministic numbers, model-written prose) is what makes citation-anchored, zero-hallucination output possible.

Statista and a raw WTTC subscription give you data tables; DataGreat turns the same WTTC release into structured, cited analysis — forecasts, benchmarks and recovery reports — in seconds. You keep the primary-source rigor but skip the manual modelling. See the side-by-side breakdowns at /vs for Statista, WTTC data and general chatbots.

A traditional tourism research engagement runs $20k–$100k and takes 4–12 weeks. DataGreat produces the same analytical lenses in under a minute against a verified public dataset for $49–$1,499 a month. It is not a replacement for bespoke strategy work, but it replaces most of the time teams lose to data-gathering and chart-building.

There are five plans. Explore is free forever (1 report/month, 5 reference countries, 1 module). Researcher is $49/month (15 reports, all 42 countries, 10 core modules). Analyst is $149/month (50 reports, all modules and presets, white-label, 3 seats). Agency is $499/month (250 reports, 10 seats, REST API). Institute is $1,499/month (1,000 reports, SSO, custom data).

Yes. The Explore tier is free forever: one report per month across five reference countries (TUR, USA, GBR, FRA, ESP), the Country Snapshot module, a watermarked web view and a Risk Radar preview. It exists so you can see exactly what a verified, citation-anchored report looks like before committing to a paid plan.

Yes. Paying annually saves two months on every paid tier — for example Researcher is $490/year instead of $588, and Analyst is $1,490/year instead of $1,788. Annual plans keep the same report quotas and feature set as their monthly equivalents; you simply lock in the lower effective rate.

Extra reports are billed per unit rather than blocking you: $5 each on Researcher, $3 on Analyst and $2 on Agency. Institute includes overage in its 1,000-report allowance. Additional team seats are similarly metered — for example $29 per extra seat on Analyst and $49 on Agency — so you scale usage without changing plans mid-cycle.

REST API access ships with the Agency tier (1,000 requests/day) and the Institute tier (10,000 requests/day). Lower tiers are web and PDF only. If you need to embed verified tourism data in your own product or pipeline, Agency is the entry point; Institute adds SSO and custom data onboarding for enterprise deployments.

Authentication runs on Supabase with row-level security on every tourism data table, and payments are processed by Stripe. Reports you generate are scoped to your account; the only publicly visible material is what you explicitly publish through a shareable link. Institute customers can add SAML SSO for centralised access control.

Yes, on the Institute tier. SAML SSO lets central banks, DMOs and research institutes manage DataGreat access through their existing identity provider, with 25 included team seats and $79 per additional seat. SSO is paired with custom data onboarding and a named support contact for enterprise governance requirements.

Register at app.datagreat.com, pick a country and a module or preset, then generate your first report — it takes about 30 seconds and the free Explore tier needs no card. See the step-by-step onboarding, including the API quickstart, on the Getting Started page at /getting-started.

Email hello@datagreat.com for sales, support or Institute-plan enquiries; the team replies in English and Turkish. The About page at /about covers the company, offices and methodology, and every tourism page links to the exact WTTC source it draws from if you want to verify a figure independently.