We mapped every vineyard in Burgundy.
We know which village wines grow 0 metres from a Grand Cru on identical limestone — and which families have worked those vines for seven generations. Now it's an API.
Gevrey-Chambertin slope profile — real data from the Burgundata API
{
"appellation": "Gevrey-Chambertin",
"classification": "premier_cru",
"climat": "Les Champeaux",
"spatial_evidence": {
"nearby_grand_crus": [
{ "name": "Chambertin", "distance_metres": 0 }
]
},
"geological_match": true,
"elevation_metres": 301.5,
"slope_degrees": 6.6,
"aspect": "northwest",
"land_value_ratio_to_grand_cru": 0.25
}Live API response. This vineyard borders Chambertin at 0 metres on identical rock.
What the data reveals
Some Premier Crus physically touch Grand Cru vineyards — same slope, same rock, same rainfall. The price difference is 10x. We measure every boundary.
The limestone beneath Chambertin doesn't stop at the appellation boundary. We know exactly where it continues — and which appellations sit on it.
Elevation, gradient, compass bearing — for every plot. The Grand Crus occupy a narrow band of the hillside. We know which appellations share that band.
Vineyard land transactions reveal what insiders believe. Some appellations trade at 20% of adjacent Grand Cru land value. The question is: why?
47 producer profiles. Generational depth, mentor lineages, winemaking philosophy. The people behind the terroir — structured and queryable.
Pricing
Built for
Enrich product pages with terroir data, geological context, and spatial relationships between appellations.
Give language models structured access to Burgundy's vineyard geography, classifications, and producer networks.
Back up recommendations with elevation profiles, geological matches, and proximity to Grand Cru vineyards.
Compare land values, track appellation pricing relative to Grand Cru benchmarks, and identify undervalued terroir.
Teach Burgundy's classification system with real spatial data instead of static maps and memorisation.