Patterns hidden in millions of location points.
A location-analytics platform that automatically surfaces movement patterns from millions of geolocation data points. Built for the questions analysts actually ask — who is moving together, who stays where, who visits regularly, who enters restricted areas.
Geolocation data is abundant. Useful geolocation intelligence is scarce — because the patterns that matter are buried in volume that no human can read sequentially. Jatayu was built around the questions analysts actually need answered: convoy detection, stationary surveillance points, regular routes, common transit hubs, group movements. Each analysis returns provenance back to the underlying records, so the intelligence is defensible — not just produced.
The signal is in the volume, not in the points.
- ▸Manual review of geolocation trails cannot scale beyond a handful of subjects, regardless of the size of the analyst team.
- ▸Movement patterns — coordination, convoys, repeated routes — are statistical, not visual, and are missed without tooling.
- ▸Common transit hubs, hideouts, or surveillance points appear only when comparing many trails against many regions.
- ▸Group and troop detection requires correlation across multiple terminals, not a single one at a time.
- ▸Field analysts need provenance back to the underlying records — opaque ML output doesn't pass review.
Eight analyses an operational analyst can act on.
Sequential path detection
Identify two or more targets travelling together or following each other — escort patterns, convoys, coordinated travel.
Stationary period detection
Terminals that remain in a confined area for extended periods — bases, hideouts, regular meeting points, surveillance.
Periodic movement pattern
Recurring travel routines and habitual routes — daily schedules, supply runs, predictable behaviour.
Area entry / exit tracking
Who enters and exits regions of interest — border zones, restricted areas, sensitive zones.
Common terminals across areas
Targets appearing in multiple distinct regions — connecting dots across seemingly unrelated locations.
Distance coefficient analysis
Rank terminals by overall travel intensity and range — long-haul couriers, high-mobility targets.
Stop point analysis
Complete movement history with identified stop points — where a target spends time and for how long.
Troop / group detection
Terminals frequently travelling together in groups of 2+ — patrol groups, coordinated units, organised activity.
Surfaces the questions analysts already ask — at scale.
- ▸Border and infiltration monitoring across high-volume data corridors.
- ▸Convoy and group detection for coordinated operations.
- ▸Surveillance-base identification through stationary-period analysis.
- ▸Routine and habitual route discovery for predictive operational planning.
- ▸Cross-region target identification — connecting otherwise unrelated movements.
- ▸Provenance-traceable outputs that hold up under operational scrutiny.