KI-Standortintelligenz

Von tausenden Standorten zur Shortlist. In Tagen.

Locations enriched with European public data sources. Analysed by multiple AI models on patterns, potential, and opportunities. For faster, defensible decisions. At scale.

analyzing0coordinates / min

Works with

ClaudeGPTGeminiMistralKadasterBAGBGTNDWPDOKBedrijfsdata.nlOpenStreetMapGoogle MapsClaudeGPTGeminiMistralKadasterBAGBGTNDWPDOKBedrijfsdata.nlOpenStreetMapGoogle Maps

So funktioniert es

Vier Schritte, wiederholbar über jeden Sektor.

Vollständige Methodik lesen
  1. 01

    Definieren Sie Ihr Set

    Laden Sie Kandidaten hoch oder definieren Sie sie nach Kriterien — z.B. alle Tankstellen in einer Region, alle Grundstücke über 500 m² in einem Engpass-Gebiet.

  2. 02

    Wir reichern automatisch an

    Katasterdaten, Demografie, Verkehr, Infrastruktur, Street View, Webdaten — standardisiert pro Standort.

  3. 03

    Mehrere KI-Modelle bewerten parallel

    Claude, GPT und Gemini bewerten gegen Ihren Prompt. Uneinigkeit markiert Standorte, die menschliche Prüfung benötigen.

  4. 04

    Shortlist mit Begründung

    Eine geordnete Liste mit Belegen pro Standort, bereit für Genehmigung, interne Freigabe oder Stakeholder-Prüfung.

Warum Locata

Drei Dinge, die einer Prüfung standhalten.

01

Insight

Decisions based on better insights.

Three AI models score every location against your criteria. Where they agree, the call is robust; where they diverge, you see exactly which candidates need human judgement — not a black-box rank, but evidence per location.

02

Speed

From thousands of candidates to a shortlist in days.

What takes months by hand runs in a sprint. Fast enough for tender deadlines, council cycles, and competitive markets where the first credible proposal wins.

03

Efficiency

More candidates scored, less work per candidate.

Locata doesn't replace expertise — it scales it. The same pipeline runs across 100 or 10,000 candidates with consistent depth, without growing team headcount linearly.

Live · Scoring-Lauf

Kandidaten für Pfandautomaten · NL

Gas station 0421 · Utrecht943/3
Transfer station 18 · Almere893/3
Roadside hub · Eindhoven873/3
Petrol plaza · Breda712/3
Service area · Zwolle582/3

Schematische Vorschau · nur indikativ

Case Study

Statiegeld Nederland.

Von über 1.000 Tankstellen- und Übergabestation-Kandidaten zu einer 100-Standort-Shortlist für Pfandautomaten. Sondierungszeit von Monaten auf Wochen reduziert. Die Methodik erstreckt sich nun auf jede angrenzende Sammelkategorie.

Bewertete Kandidaten
1,000+
Shortlist-Größe
~100
Zeit bis Shortlist
3 Wochen
Sondierungsreduktion
10×

FAQ

Häufige Fragen zu Locata.

  • What is Locata?

    Locata is an AI-powered location intelligence platform that scores thousands of candidate locations against custom criteria. Three frontier models (Claude, GPT, Gemini) run in parallel against European public data — Kadaster, BAG, BGT, BRO, NDW, PDOK — to produce a ranked shortlist with reasoning per location.
  • Who uses Locata?

    Grid operators (Liander, TenneT, Stedin, Enexis) for substation and transformer siting; EV charging operators (Fastned, Allego, Powerdot) for charge point placement and concession bids; Statiegeld Nederland for bulk deposit return machine rollout; municipalities and consultancies for shared mobility hub networks; and retail chains like McDonald's for new-store site selection.
  • How is Locata different from Placer.ai, CARTO, or Esri?

    Locata is purpose-built for European infrastructure rollouts, not US retail foot-traffic analysis. We run multi-model AI scoring instead of single-vendor confidence, integrate natively with Dutch and EU public data sources (Kadaster, BAG, BGT, NDW, PDOK), and ship per-location reasoning that holds up in ACM consultation and municipal council review — not just a heatmap.
  • What data does Locata enrich each location with?

    Cadastral records (Kadaster), buildings and addresses (BAG), large-scale topography (BGT), subsurface registry (BRO), traffic intensity (NDW), national geo-portal (PDOK), CBS demographics, grid operator public capacity indicators, Google Street View, aerial orthophotos, OpenStreetMap, and per-vertical sources like RDW EV density or municipal plankaarten. All enrichment is standardised across candidates, so locations are comparable on the same axes.
  • How fast is a Locata engagement?

    A typical pilot delivers a scored shortlist in two to three weeks from kickoff — week one for prompt definition and data integration, weeks two-three for the scoring run and reasoning review. Ongoing subscriptions support continuous evaluation as new candidates emerge across investment-plan or expansion cycles.
  • How much does Locata cost?

    Pilot engagements start at €15,000 fixed-scope, fixed-price. Ongoing subscriptions start at €2,500/month with quarterly refresh cadence. Enterprise engagements for grid operators and major retail chains are scoped per program — talk to us about scope, integration, and timing.
  • Is Locata GDPR compliant?

    Yes. All processing happens under GDPR with EU data residency. Customer candidate sets, scoring prompts, and outputs are never used to train public AI models — inference only, audit-logged. ISO 27001-aligned processes, available DPA, sub-processor list provided per engagement.
  • Can Locata integrate with our internal GIS?

    Yes. Locata exports to GeoJSON, CSV, PDF, and a REST API. We integrate with ESRI/ArcGIS, FME, internal asset-management systems (Maximo, IFS), and project-portfolio platforms via export or API. Your single source of truth stays where it is — Locata feeds it.

Kontakt aufnehmen

Was würden Sie scannen?

Erzählen Sie uns von Ihrem Rollout — Kandidatenset, Kriterien, Deadline. Wir melden uns innerhalb eines Werktages.

Sample run on your data within 5 working days

EU-ansässig, DSGVO-konform standardmäßig

Keine Verpflichtung, kein Vertrag bis zur Pilotphase

Mit dem Absenden stimmen Sie unserer Datenschutzrichtlinie.