Pushing The Envelope
Embodied AI Agents for Land, Terrain, and Mission Intelligence
Pushing The Envelope
Embodied AI Agents for Land, Terrain, and Mission Intelligence
Embodied AI Agents for Land, Terrain, and Mission Intelligence
Embodied AI Agents for Land, Terrain, and Mission Intelligence
L10X AeroInnovations is an innovation-first company developing embodied AI agents that learn from the land in real time.
Our proprietary agents — OPTIMA™, VISION™, and LANTIS™ — evolve through real-world missions, integrating perception, memory, and decision-making to optimize outcomes across agriculture, terrain analytics, and autonomous mission planning.
We design systems that don’t just operate — they observe, learn, and improve with every mission.
“I founded L10X to pioneer systems that don’t just operate — they adapt, learn, and evolve with the world they serve. As global pressures reshape how we grow food, manage land, and plan missions, the need for intelligent systems that respond in real time has never been greater.
Drawing from decades in aerospace and national security, I built L10X to bring this intelligence down to earth — equipping growers, stewards, and planners with tools that see deeper, learn faster, and help forge a more resilient future.
We start with the land beneath our feet — but the systems we’re building are designed to scale across missions, from rural farms to contested terrain to planetary surfaces.”
We develop adaptive robotic systems powered by embodied AI agents — intelligent teammates that learn from physical missions to enhance performance over time.
OPTIMA™ and VISION™ aren’t just algorithms — they are learning AI agents, evolving with every mission they fly.
We apply aerospace-grade tools and AI agents to support local growers and land managers with actionable insight — not complexity.
This track keeps our systems grounded — and our innovation focused on real-world value.
Optimized Parametric Intelligent Mission Assistant
An adaptive AI planning and feedback agent that refines flight, mapping, and mission strategies through embodied learning and real-time performance analysis.
Vegetative Insight via Spectral Indices and Optimization Network
A multi-layered embodied AI agent that uses RGB-based indices to detect plant stress, disease, canopy shifts, and pest signatures — optimized for vineyards, farms, and natural ecosystems.
Learning Agent for Nonlinear Terrain Intelligence Systems
A terrain-aware modeling agent trained on high-resolution surface and elevation data to identify ingress paths, erosion risk, runoff channels, and landscape-driven mission constraints.
Mapping 100 acres of hay and mixed-use farmland to detect slope-driven stress and guide more efficient use of resources.
Our maps supported erosion control and replanting efforts in a conservation garden — highlighting terrain and canopy zones for resilient design planning.
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