Building agents that need real-world grounding beyond text retrieval. You want to know how MCP wires into your existing stack.
Tired of ETL pipelines for every new use case. You want one connector that gives every analyst and model live access to location, mobility, and POI data.
Owning roadmaps for AI features, internal copilots, or customer-facing agents. You want to see what’s actually shippable next quarter.
“Where should we open our next 5 stores in Texas without cannibalizing existing ones?”
Site scoring, trade area overlap, foot traffic forecasts, in one agent thread.
“Which billboards in Mumbai actually reach finance professionals aged 30–45?”
Audience reach modeling, dwell-time scoring, campaign planning by panel.
“Score every parcel in this 5-mile radius for a quick-service tenant.”
Parcel-level demand modeling, comp visit data, lease-up risk in seconds.
“Find every café within 1km of a metro station that doesn’t stock our SKU.”
Distribution gap analysis, prospecting lists, on-shelf availability by geo.
“Which of our branches are losing share to a competitor opened last year?”
Branch performance vs visit data, network rationalization, geo-fraud signals.
“Where should we place the next dark store to cover 90% of demand?”
Depot placement, last-mile density, hour-by-hour demand patterns.
“Build me an audience of people who visit Whole Foods 3+ times a month.”
Visit-based audience enrichment, geo-targeting, physical-visit attribution.
“Which neighborhoods saw the biggest drop in retail activity last quarter?”
Mobility-based economic indicators, policy impact, infrastructure prioritization.
“Show me where our 5G coverage misses the highest-traffic commute corridors.”
Mobility-based economic indicators, policy impact, infrastructure prioritization.
How different roles and industries will use this.
Where the gap shows up first: retail expansion, OOH planning, real estate scoring, fleet & logistics, insurance underwriting, urban planning.
The 12 data layers your agent gets through one connector — POI, People, Consumer, Mobility, Visit, Web, IP Geolocation, and more. How they map to common business questions.
What it is, how it works, and what wins (and lessons) from existing MCPs in the market. No jargon — built so a CMO and an ML engineer leave with the same mental model.
AI/ML engineers, data/analytics leads, and product/strategy teams — one concrete workflow for each. Same data, different angle of attack.
Five live use case patterns — site scoring (Retail), OOH planning (Media), trade area analysis (CRE), prospecting (CPG), competitive mapping (any vertical) — each with the exact prompt and output.
We pull a site selection or OOH problem from registrant submissions and solve it live in an MCP-connected agent. You see the real process, not a polished walkthrough.
Bring your stack questions, your integration questions, anything.
Date
June 24, 2026
Wednesday
Time
2:00 PM ET
45 mins + Q&A
Format
Live + Demo
Recording sent post-event
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