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USE CASE
Forward Airfield Security
The Situation: A Contingency Response Wing deploys to an austere airstrip. Dense vegetation surrounds the perimeter on three sides. The threat: adversary personnel or vehicles approaching through the tree line.
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Why Current Solutions Fail: Fixed cameras can't see through foliage. Manned patrols can't cover the full perimeter. Traditional drone reconnaissance shows leaves, not what's beneath them. And flying multiple platforms in tight airspace risks mid-air collisions.
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The Mazer Intel Solution: A swarm deploys from a compact ground station and self-distributes around the perimeter. Computational imaging fuses multiple perspectives to detect heat signatures beneath the vegetation. Distributed AI keeps the platforms from colliding. Operators see actionable alerts, not raw sensor feeds.
Outcome​
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Persistent 360° perimeter coverage
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Detection through dense vegetation
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Safe multi-platform coordination
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Works without constant comms
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Reduces manpower for security patrols
USE CASE
Wilderness Search & Rescue
The Situation: Hikers are missing in a national forest. Time is critical. The search area is thousands of acres of dense tree cover.
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Why Current Solutions Fail: Helicopters with FLIR can only see heat signatures in clearings. Ground teams move slowly and can only cover limited terrain. A person lying injured beneath the canopy is invisible to overhead thermal sensors—even if they're 20 feet from the flight path.
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The Mazer Intel Solution: Multiple drones scan the forest in coordinated patterns. Our imaging reconstructs what's beneath the canopy, finding body heat that single-frame thermal would miss. Distributed coordination ensures efficient coverage without gaps or collisions. Search time drops from days to hours.
Outcome​
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Find survivors beneath tree cover
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Cover large areas quickly
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Coordinate multiple aircraft safely
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Works day or night
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Reduce search time by 10x or more
USE CASE
Border Security
The Situation: Dense vegetation lines a contested border region. Illegal crossings, smuggling routes, and potential threats move through terrain that defeats conventional surveillance.
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Why Current Solutions Fail: Fixed tower cameras have limited range and can't see through foliage. Ground patrols can't cover vast stretches of terrain. Traditional aerial surveillance shows tree canopy, not what moves beneath it.
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The Mazer Intel Solution: Coordinated drone swarms with canopy-penetrating sensors detect movement beneath vegetation across wide border zones. Distributed AI coordinates persistent coverage without the collision risks of dense multi-platform operations.
Outcome​
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Detect movement through dense vegetation
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Persistent wide-area coverage
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Safe multi-aircraft coordination
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Works day or night in remote terrain
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Force multiplication for border agents
USE CASE
Reconnaissance Under Canopy
The Situation: Intelligence requirements in a region dominated by jungle or dense forest. Targets move beneath the canopy. Adversaries know that overhead assets can't see them under the trees.
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Why Current Solutions Fail: Predators and Reapers were designed for deserts. Their sensors show canopy, not what's beneath it. Signals and human intelligence help, but there's no substitute for eyes on target. And traditional platforms are expensive, centralized, and vulnerable.
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The Mazer Intel Solution: Distributed, expendable platforms with canopy-penetrating sensors. See beneath the jungle. Cover wide areas with coordinated swarms. Lose a platform without losing the mission. Operate in comms-degraded environments where traditional platforms fail.
Outcome​
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Reconnaissance capability in denied terrain
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Distributed = resilient
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Works in comm-degraded environments
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Lower cost than traditional platforms
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Attritable without mission loss
USE CASE
Critical Infrastructure Protection
The Situation: A power plant, data center, or water treatment facility surrounded by wooded terrain. Security needs to detect intrusion before threats reach the fence line, not after.
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Why Current Solutions Fail: Fixed cameras only see their narrow field of view. Security patrols are predictable and can't cover everything. Intruders use the tree line for concealment during approach. By the time they're visible, they're already at the perimeter.
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The Mazer Intel Solution: Persistent autonomous patrols that see through the surrounding vegetation. Detect approaches hundreds of meters out, while intruders still think they're hidden. Automatic alerts with fused imagery, not just "motion detected."
Outcome​
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Early warning before perimeter breach
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See through surrounding vegetation
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Unpredictable patrol patterns
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Reduced security manpower costs
USE CASE
Natural Language Mission Planning
The Situation: A special operations team needs to coordinate multiple drones for a complex mission: perimeter surveillance, avenue of approach monitoring, and target building observation. The operator is task-saturated, wearing gloves, and needs to issue commands to ten platforms with different objectives.
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Why Current Solutions Fail: Proprietary mission planning software only works with specific drone brands. Manual waypoint entry is slow and error-prone under stress. Typing is impractical with gloves or in low-light conditions. And most systems require constant network connectivity to cloud servers.
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The Mazer Intel Solution: Voice-driven mission planning that understands operational terminology. Say "Drones one and two, fly to building 107 at 1,000 feet, maintain 100-foot separation, orbit five times" and the system generates executable flight plans. Works with any MAVLink-compatible platform. Runs on edge hardware when networks are unavailable.
Outcome​
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Voice commands eliminate manual waypoint entry
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Understands military brevity and standard formats
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Works across drone manufacturers
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Operates disconnected from cloud infrastructure
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Reduces mission planning time from hours to minutes
All of these solutions depend on two breakthrough technologies: computational imaging that sees through occlusions, and distributed AI that coordinates at scale.
Mazer Intel can provide breakthrough imaging capabilities to see through forest canopy.