Skylarklabs
Skylark Labs · Ground Infrastructure AI

TERRA

Terrain, Environment, Roads, Runways & Assets — the adaptive intelligence layer that learns from real-world conditions after deployment, and shares that knowledge across every connected asset.

<1%
False
positive rate
5
Operational
domains
$250B
Addressable
market
2+
Years
In field ops

"Most ground infrastructure AI stops learning the moment it is deployed. TERRA does the opposite."

Amarjot Singh — Founder & CEO, Skylark Labs

Deployed across defense airfields, national highways, smart cities, and automotive partners including Indian Navy, INDOT, Mercedes-Benz, and NHAI.

On-device adaptive intelligence for ground infrastructure.

Across highways, runways, tarmacs, and carrier decks, hazards emerge between inspection cycles while conditions evolve faster than static monitoring systems can adapt. Roads crack, debris accumulates, and surface conditions shift in ways frozen models were never designed to learn from.

TERRA addresses this gap. It builds local operational memory from every environment it encounters — debris signatures, false positives, surface anomalies, shifting conditions — then shares those learnings across the network without the underlying raw data ever leaving the originating asset.

Surface Signals
Identifies and learns new field signals on-device from minimal examples — refining debris detection, surface anomaly classification, and hazard recognition without retraining cycles or cloud dependency.
Infrastructure Policies
Refines monitoring, alerting, and maintenance response behavior based on operational conditions — with reduced operator dependency across distributed infrastructure.
TERRA ARCHITECTURE FIXED FOUNDATIONAL MODEL PERCEPTION CONTROL ON-DEVICE LEARNING PERCEPTION CONTROL
Fleet Learning

Baseline and adaptive capabilities across detection and control.

Detection — Trained Signal Categories

Riyadh — Urban Monitoring

FOD Detection

Ground Autonomy

CAPABILITIES Surface Detection Real-time FOD, crack & debris ID Adaptive Learning On-device model refinement Fleet Intelligence Cross-asset knowledge sharing SENSORS EO / IR Camera Day/night visual & thermal A LiDAR Scanner 3D point-cloud profiling B Ground Radar All-weather subsurface detection C

A $250 billion opportunity structurally underserved by static AI.

$14B
FOD detection market

Global foreign object debris detection — growing with commercial aviation expansion and increased defense airfield activity worldwide.

$66B → $165B
Smart highway & mobility intelligence

Today's market projected to reach $165B by 2030, driven by aging infrastructure mandates and the shift to real-time road intelligence.

10%
Infrastructure monitoring CAGR

The broader infrastructure monitoring market growing at 10% annually — every segment demanding intelligence that learns in the field, not in the lab.

Proven across five domains,
two continents.

Defense forces, government agencies, and private operators across the United States, India, the Middle East, and Europe.

Defense / Runway
Indian Navy Airfields — Tracer AI Vehicle

Two years of operational deployment achieving sub-1% false positive rates where oil patches, ground crew movement, and variable lighting defeat conventional FOD detection.

Naval / Carrier
Indian Navy Aircraft Carrier

Carrier deck validation under salt spray, vibration, and high operational tempo at sea — among the most demanding environments for any surface AI.

Airfield / Airport
Indian Air Force & GMR Hyderabad International

Fixed FOD systems running 24/7 at air force bases and a major international airport, continuously learning from each site's unique conditions.

U.S. Defense
Defense Innovation Unit & U.S. Air Force

Post-deployment learning architecture demonstrated to DIU and USAF stakeholders. Described as "a game-changer for defense operations."

INDOT Highway
Highway
Indiana Department of Transportation — Highway Corridors

Scout Towers deployed across Indiana's busiest corridors, learning traffic patterns, infrastructure stress indicators, and maintenance signals in real time.

NHAI Vehicle Counting
Traffic Intelligence
NHAI — National Highways Authority of India

Real-time vehicle counting, classification, and flow analytics across national highway corridors, enabling adaptive traffic management at scale.

Urban Monitoring
Riyadh Green City — Road Monitoring

Continuous surface and traffic monitoring across Riyadh's Green City development, supporting smart city infrastructure with adaptive real-time intelligence.

Automotive
Mercedes-Benz R&D India — Accident Intelligence

Adaptive AI onboard vehicles generating a live Accident Awareness Score by fusing edge AI, telematics, and geographic analytics.

Road Monitoring
AMNEX x NHAI — Road Defect Monitoring

Continuous surface defect detection across national highway corridors, enabling proactive maintenance before failures escalate.

Traffic Enforcement
Fovea — Traffic Violation Detection

AI-powered detection of traffic violations at scale — wrong-way driving, signal jumping, lane violations — part of the $21M law enforcement network spanning 6,000 assets across Asia.

"The future of ground infrastructure intelligence will be defined by whether the AI layer monitoring these systems can keep learning in the real world."

AMARJOT SINGH — FOUNDER & CEO, SKYLARK LABS

Every ground asset, getting smarter every day.

See how TERRA's adaptive intelligence layer performs in your operational environment.