Offline Geocoding & Address Search

Convert addresses to map coordinates without any internet connection. Powered by OpenAddresses open data and DuckDB Spatial, the Offline Geocoding module enables single-address lookup, bulk batch processing, and reverse geocoding — all on-device in denied environments.

Why Offline Geocoding Matters

In DDIL (denied, degraded, intermittent, limited) environments, address-to-coordinate conversion is typically impossible without internet access. Tactical AI DuckDB eliminates this dependency by embedding a local OpenAddresses dataset pre-indexed in DuckDB Spatial for sub-second lookups against hundreds of millions of address records — entirely offline.

🏠 Field Address Lookup

An emergency management team receives a list of 500 addresses in an affected area and needs to plot them on the map for resource allocation. Using Batch Geocoding, all 500 addresses are geocoded in seconds against the local OpenAddresses dataset, creating map markers with occupancy and address data — with no connectivity required.

OpenAddresses Dataset

The geocoding engine is powered by OpenAddresses — the world's largest open dataset of address points collected from authoritative government sources. Regional datasets are downloadable in advance for pre-staging before deployment.

OpenAddresses Coverage

Geocoding Modes

Three geocoding modes cover all field use cases from single address lookups to large-scale batch processing:

Mode Description Best For
Interactive Type address, get coordinate instantly with map preview Single lookups, navigation waypoints
Batch (CSV) Upload CSV with address column, download coordinates Pre-staging large address lists
Reverse Tap map or enter coordinates, get nearest address Identifying locations, incident reporting

Coordinate Systems Supported

All geocoding results are available in multiple coordinate reference systems to match your operational workflow:

Output Coordinate Formats

Batch Geocoding with DuckDB

Large-scale batch geocoding leverages DuckDB's columnar processing engine. Input CSV files with thousands of addresses are processed using parallel SQL joins against the OpenAddresses spatial index, returning results in seconds rather than minutes.

Dataset Size Estimated Processing Time Device
100 addresses < 1 second Any Android 8+ device
1,000 addresses 2-5 seconds Any Android 8+ device
10,000 addresses 15-30 seconds Snapdragon 8-series recommended
100,000 addresses 2-5 minutes High-performance device

Online Geocoding Fallback

When connectivity is available, the geocoder can optionally augment OpenAddresses results with online services for higher accuracy or coverage in regions where local data is limited:

Online Geocoding Services (Optional)

Geocoding in AI Workflows

The AI Agent integrates with the geocoding engine, enabling natural language location resolution. When you ask "Navigate to 123 Main Street," or "Mark the building at the intersection of Oak and Elm," the AI automatically resolves the address to coordinates using the offline geocoder and performs the requested action.

🤖 AI + Geocoding Integration

During route planning, the AI Agent geocodes multiple waypoints from a verbal briefing: "Plan a route from the staging area at 100 Industrial Drive to the checkpoint at 450 Highway 35, then to the forward operating base at grid 37SED 123 456." All three location types (address, address, MGRS) are resolved automatically.

Dataset Management

Geocoding datasets are downloaded per region before deployment and stored on-device. The Dataset Manager shows download status, storage usage, and allows updating when connectivity is available.

Region Approx. Download Size Record Count
Single US State (e.g. Texas) ~200 MB ~12M addresses
Full US Coverage ~4 GB ~150M addresses
European Country 100-500 MB 5-40M addresses
Custom AOI Variable Area-dependent
OpenAddresses DuckDB Spatial MGRS UTM Batch Processing Reverse Geocoding 100% Offline
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