SOLUTION BY ROLE
xMap for Data Scientists
Production-grade physical world data, structured for the workflows you actually run — not the dashboards you never open.
300M+
POIs globally indexed
98%
US parcel coverage
5 SDKs
Python, TS, Go, Rust, Swift
<60s
First query
WHAT DATA SCIENTISTS USE xMAP FOR
Eliminate the 60-80% overhead
before modeling starts.
Data scientists working on location-influenced models spend most of their time acquiring, cleaning, and joining geographic data. xMap eliminates that overhead with a single, clean, versioned data layer purpose-built for analytical consumption.
THE DATA
Every layer, analyst-ready.
Schema-stable, versioned, and built for ML feature engineering and statistical analysis.
📍
poi
Structured points of interest with category, brand, coordinates, hours. Schema-stable. Agent-ready.
🚗
car_traffic
Road segment volumes and speeds. Hourly resolution. Direction of travel. Timeseries for ML feature engineering.
📡
gps_mobility
Aggregated origin-destination flows, dwell time, visit frequency. Privacy-safe. Population-level.
🏛
parcel_data
Ownership, zoning, assessed value, structure type. 98% US coverage. Versioned snapshots for longitudinal analysis.
👥
demographics
Block-group level population, income, age, household composition. Joinable on GEOID. Updated on census cycle.
💻
sdk_access
Python, TypeScript, Go, Rust, Swift SDKs. Identical method names and response shapes. Full async support.
WORKFLOWS
What data scientists build on xMap.
01
Demand Forecasting Models
Build location-influenced demand models using xMap’s mobility, demographics, and POI layers as structured ML features.
- POI density features by category and radius
- Traffic percentile rank by city
- Mobility-derived trade area catchment
- Demographic composite scores at block-group
02
Site Scoring & Risk Models
Score candidate locations against custom site criteria models with reproducible training sets from versioned xMap snapshots.
- Versioned data for reproducible training sets
- Parcel velocity as leading indicator of change
- Competition pressure index by brand tier
- Agent confidence vs. outcome correlation
03
Network Optimization
Optimize hub placement, route design, and service territory coverage using real traffic and population movement data.
- Drive-time isochrone calculation at scale
- Batch distance matrix for thousands of nodes
- H3 hexagonal grid for mobility aggregation
- Async batch processing with Python SDK
PYTHON SDK IN ACTION
Five lines to your first site score.
The xMap Python SDK is designed for the workflows data scientists actually run. Full async support, GeoPandas-compatible output, versioned snapshots for reproducible training sets.
SDK WORKFLOW · Site scoring with Python
pip install
pip install xmap-sdk · installs in 12s · no system dependencies
✓agent.evaluate()
parcel, objective, layers, radius_m · returns decision + confidence + trace
✓layers.parcels()
GeoDataFrame output · EPSG:4326 · GeoPandas-compatible · ST_DWithin supported
✓snapshots.get()
Versioned snapshot · 2020-2024 history · reproducible training sets · GEOID joinable
✓batch.score()
4,200 parcels scored · async · 90 minutes · full reasoning trace per site
DONEINTEGRATION
Works with your existing stack.
From Jupyter notebooks to production pipelines, xMap fits where data scientists already work.
Python
Python SDK
pip install xmap-sdk. GeoPandas-compatible output. Five SDKs total: Python, TypeScript, Go, Rust, Swift.
SQL
SQL / Warehouse
Versioned snapshots in Snowflake, BigQuery, Databricks. GEOID-joinable. ST_DWithin and ST_Intersects supported.
REST
REST + GraphQL
High-throughput API. p95 latency under 200ms. Full async support for batch scoring at national scale.
MCP
MCP Server
For AI agents using Claude or other LLMs. Pre-configured tool definitions. Zero routing code required.
LOGISTICS PLATFORM · HEAD OF DATA SCIENCE
-22% delivery time+11pts NPS$48M route savings50 metros
“xMap gave us ground truth on traffic patterns we could not get anywhere else at this resolution. Our routing model improved 22% in the first month.”
— Head of Data Science, Logistics Platform
Ready to bring xMap into your models?
pip install xmap-sdk and first query in under 60 seconds.
Get in Touch
Whatever your goal or project size, we will handle it.
We will ensure you 100% satisfication.
sales@xmap.ai
+1 (415) 800-3938
800 North King Street Wilmington, DE 19801, United States
1 Chome-17-1 Toranomon, Minato City, Tokyo 105-6415, Japan
"We focus on delivering quality data tailored to businesses needs from all around the world. Whether you are a restaurant, a hotel, or even a gym, you can empower your operations' decisions with geo-data.”
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