Deep Tech · Neuromorphic Computing · Boca Raton, FL

The machine that
thinks at the
speed of physics.

We build computing systems that react faster than any digital processor can clock — not by running faster software, but by eliminating software from the critical path entirely.

Resonant field surface
Pattern Memory · Analog Intelligence

Recognition does not begin with search.

Your brain does not store memories as files or retrieve them from a database. It stores patterns — spatial, temporal, and sensory at once. And it recognizes what is familiar almost instantly, even from a partial signal, even years later.

Modern machines work in a fundamentally different way. They compute, classify, and query servers. It works — but it consumes enormous resources, depends on connectivity, and does not adapt to a specific person.

We are building a computing medium in which intelligence emerges from the physics of an analog field — much as it does in living systems. No central processor in the critical path. No cloud dependency. No retraining cycle.

<1μs response latency 0 digital logic in critical path 65,536 parallel resonators 10× power efficiency vs GPU DARPA BAA submission June 2026 $1.25M seed round <1μs response latency 0 digital logic in critical path 65,536 parallel resonators 10× power efficiency vs GPU DARPA BAA submission June 2026 $1.25M seed round

Technology advantages

Physics-native computation

Computation emerges from coupled resonant systems instead of sequential software execution.

Ultra-low latency

Response occurs at physical signal propagation speed — no clocks, no instruction queues.

Energy efficiency

Field dynamics process information continuously without the overhead of digital instruction loops.

Graceful degradation

Resonant fields tolerate component failure without catastrophic collapse — inherently fault-tolerant.

ASIC-ready

The 256×256 LC oscillator array maps directly to standard semiconductor fab processes.

Beyond von Neumann

Memory and processing unified in the field — a fundamentally different computing paradigm.

Human-safe humanoid systems

Because decision-making occurs inside stable physical architectures rather than opaque software stacks, this technology opens the path toward the first generation of truly safe humanoid robots designed to work alongside humans.

Humanoid robot
Sub-microsecond reflexes
Collision avoidance below the latency threshold of any digital control loop.
Full-body coordination
Thousands of joints managed by a single resonant field — no scheduling conflicts.
Low power, high endurance
Orders of magnitude less power than GPU-based inference for equivalent tasks.
Safe by design
Stability is a physical property of the architecture — not a software guarantee.
Learns from the person, not a dataset
Builds a user model through experience — no retraining, no cloud.
Recognizes intent, not just state
Detects the beginning of a fall before it completes — not the final frame.
Always-on, always-local
Full cognitive function without network connectivity. No exceptions.
Experience transfers between units
Patterns from one unit copy directly to the next — personalization from day one.
No network attack surface
No IP address on the critical path. Remote compromise is physically impossible.

For investors

Validated simulations demonstrate stable resonant fields across 65,536 resonators. DARPA DSO BAA submission in progress (HR001125S0013, June 2026). The architecture targets the control layer of autonomous systems — a segment with no current analog-native solution at scale.

65,536
Resonators
Simulated field, validated stability
<1μs
Latency
Physical response, no software overhead
$1.25M
Seed Round
FPGA prototype + DARPA follow-on
June '26
DARPA BAA
HR001125S0013 deadline
Milestone Status Notes
Architecture design (256×256 LC array) Complete Full specification documented
Field simulation (65K resonators) Complete Stable resonant patterns validated
DARPA DSO BAA submission In progress HR001125S0013 — deadline June 2026
FPGA proof-of-concept (600 oscillators) Planned Seed funding milestone
ASIC tape-out Planned Post-seed / Series A
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Ready to learn more?

We're building the control layer for the next generation of autonomous systems. Investors, defense programs, robotics companies — let's talk.

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