Answer 6 questions. We'll build the rest.

No tech background needed. About 90 seconds.

  1. Plain English. The result you'd be proud of.
  2. Fill out the 5 above, then press Generate.
Scientific Research • Coming Soon

AI That Powers Itself

Self-powering distributed inference mesh. No cloud. No grid. Just ambient energy and intelligence.

Patent Pending  •  Application #64/012,740

Explore the Science
0W
Grid Power
0%
Cloud Dependency
Uptime Potential
9th
RLL Patent

Intelligence Without Infrastructure

Today's AI requires massive data centers, reliable power grids, and constant internet connectivity. That excludes most of the world.

Ambient Harvest reimagines computation from first principles. What if AI devices could harvest the energy they need from their environment—solar photons, ambient radio frequencies, thermal gradients, mechanical vibrations—and run inference locally using analog physics instead of digital transistors?

The result: a self-organizing mesh of intelligent nodes that requires no external power, no cloud connection, and no centralized coordination. AI that can exist anywhere—remote classrooms, disaster zones, autonomous robots, or developing nations where infrastructure doesn't yet reach.

This is not incremental improvement. This is a new computational paradigm.

Four Breakthroughs in One System

Each pillar of Ambient Harvest represents a distinct area of active research, unified by a single architectural vision.

Ambient Energy Harvesting

Multi-modal energy scavenging from four ambient sources simultaneously: photovoltaic (solar), rectenna (RF), thermoelectric (thermal gradients), and piezoelectric (vibration). Adaptive power management dynamically allocates harvested energy across computation, communication, and storage based on real-time availability.

Photovoltaic RF Rectenna Thermoelectric Piezoelectric

Analog In-Memory Compute

Resistive RAM (memristor) crossbar arrays perform matrix-vector multiplication in the analog domain—the core operation of neural network inference—using Ohm's law and Kirchhoff's current law. Orders of magnitude more energy-efficient than digital von Neumann architectures. Computation happens where data lives.

Memristor Crossbar ReRAM Analog MVM In-Situ Compute

Entropy-Gradient Routing

A thermodynamics-inspired algorithm that routes partial inference results through the mesh by following entropy gradients. Work flows naturally toward nodes with the highest available energy and lowest computational entropy—like water flowing downhill. No central scheduler required.

Entropy Minimization Gradient Descent Gossip Protocol Free Energy Principle

Self-Organizing Mesh

Nodes autonomously discover peers, negotiate capabilities, and form computation clusters without any central coordination server. The mesh self-heals when nodes fail, self-scales when new nodes join, and self-optimizes inference distribution based on real-time energy budgets and network topology.

Peer Discovery Byzantine Fault Tolerance Auto-Scaling Zero-Config

Where Self-Powering AI Changes Everything

When intelligence requires no infrastructure, entirely new use cases become possible.

🎓

Education

Bring adaptive learning tools like CoinQuest to off-grid schools. Solar-harvesting mesh nodes deliver AI tutoring without internet, electricity, or cloud accounts. Every child, everywhere.

🤖

Autonomous Robotics

LUMEN-class robots with perpetual inference capability. Harvest energy from vibration and thermal differentials during operation. No charging stations. No return-to-base cycles.

🌡

Disaster Response

Deploy intelligent sensor meshes in disaster zones where infrastructure is destroyed. Nodes harvest ambient energy to coordinate search patterns, triage resources, and relay communications.

🌎

Developing Nations

Leapfrog traditional computing infrastructure entirely. Self-powering AI mesh brings agricultural intelligence, health diagnostics, and financial literacy to communities without reliable power or internet.

Protected Research

Our innovations are protected by a growing patent portfolio covering the full stack of self-powering distributed AI.

⚖ Patent Pending

Patent #9 — Ambient Harvest

"Distributed Ambient-Energy-Harvesting Inference Mesh with Entropy-Gradient Routing and Analog Resistive In-Memory Computation"

Application #64/012,740  •  Filed March 21, 2026

9
Patents filed in the
RLL portfolio to date

From Theory to Field Deployment

A multi-year research program building toward commercially viable self-powering inference hardware.

Phase 1

Theoretical Framework

Mathematical modeling of entropy-gradient routing algorithms. Simulation of multi-modal energy harvesting budgets. Memristor crossbar array design for target neural architectures. Patent filings and literature review.

Current Phase
Phase 2

Prototype Development

Fabrication of single-node prototypes combining energy harvesting front-end with analog compute back-end. Bench testing of individual subsystems. Initial two-node mesh communication protocols.

Phase 3

Field Testing

Deployment of 10-50 node mesh in controlled outdoor environments. Measurement of energy harvesting yields across seasons and geographies. End-to-end inference latency and accuracy benchmarks under real-world conditions.

Phase 4

Production & Partnerships

Manufacturing partnerships for volume production. Application-specific mesh configurations for education, robotics, disaster response, and agricultural intelligence. Commercial deployment with pilot partners.

Follow Our Research

Be the first to receive published papers, prototype updates, and partnership opportunities as Ambient Harvest progresses from theory to reality.

Research updates only. No spam. Unsubscribe anytime.

Test Lab
Progress saved