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SYNAPLEX™ SAVUNMA APPLICATIONS

Defence Applications

70% Revenue Share | $280M Serviceable Market

>500 kGy Rad Tolerance
<10 fJ Per Synaptic Event
97.3% Accuracy
ISS Validated

Radiation-Hardened AI Portfolio

SYNAPLEX is a polymer substrate for neuromorphic computing that enables AI in radiation-intensive environments. ISS-validated (Experiment ID 8071) with greater than 500 kGy tolerance where silicon fails at less than 100 kGy.

Defence applications represent 70% of SYNAPLEX revenue projection, driven by satellite mega-constellations requiring edge AI and tactical systems operating in contested electromagnetic environments.

Our ITAR-free UK origin enables direct export to allied nations without State Department involvement, providing significant time and cost advantages for multinational programmes.

Why Silicon Fails in Space

Van Allen Belt radiation degrades conventional silicon-based neuromorphic chips

Radiation Environment

Van Allen radiation belts expose LEO satellites to 10-100 kGy total ionizing dose over 5-year mission life. Silicon neuromorphic chips experience threshold voltage shifts and increased leakage current, degrading synaptic weight precision.

50,000+ LEO satellites planned by 2030 (Starlink, OneWeb, Kuiper) require edge AI for autonomous collision avoidance and payload processing without ground station latency.

Silicon Limitations

Intel Loihi, IBM NorthPole, and BrainChip Akida all use CMOS silicon substrates that fail at less than 100 kGy. Radiation-hardened variants reduce performance by 3-5 generations and increase cost 10-15x.

SYNAPLEX polymer substrate maintains integrity beyond 500 kGy without performance degradation, enabling commercial-off-the-shelf neuromorphic integration for space applications.

Space Autonomy
$150M SAM

Space Autonomy

Edge AI substrate for autonomous satellite operations, collision avoidance, and payload processing in mega-constellations.

Target Programmes:
  • Starlink Gen2 — 30,000 satellites
  • OneWeb Phase 2 — 6,372 satellites
  • Kuiper — 3,236 satellites
  • Military Constellations — SDA Layer 1
View Space Solutions
Tactical Counter-UAS
$50M SAM

Tactical Counter-UAS

Edge AI for drone swarm engagement in EMP-contested environments with less than 10 fJ per synaptic event power efficiency.

Target Applications:
  • Swarm Classification — Real-time threat ID
  • Engagement Prioritization
  • EMP-Hardened Operation
  • Network-Degraded Mode
View C-UAS Solutions
Missile Guidance
$40M SAM

Missile Guidance

Active seeker processing for imaging infrared and millimeter-wave guidance in terminal phase engagement.

Target Systems:
  • IIR Seeker Processing
  • MMW Target Classification
  • Countermeasure Rejection
View Guidance Solutions
Nuclear Monitoring
$25M SAM

Nuclear Monitoring

IAEA safeguards and power plant monitoring with sustained operation in high-radiation environments.

Applications:
  • IAEA Verification
  • Reactor Monitoring
  • Waste Processing
View Nuclear Solutions
Satellite Processing
$10M SAM

Satellite Processing

On-orbit Earth observation and SAR processing with edge AI for immediate ground delivery.

Missions:
  • EO Classification
  • SAR Target Detection
  • Hyperspectral Analysis
View Satellite Solutions
Battlefield AI
$5M SAM

Battlefield AI

Distributed sensor networks for tactical situational awareness in network-degraded environments.

Capabilities:
  • Acoustic Classification
  • EO/IR Tracking
  • Edge Fusion

Competitive Comparison

Silicon neuromorphic chips fail at less than 100 kGy radiation exposure

PlatformTypeRad TolerancePower/EventSpace-Ready
SYNAPLEXPolymer Substrate>500 kGy<10 fJYes
Intel Loihi 2Silicon Chip<100 kGy23 fJNo
IBM NorthPoleSilicon Chip<100 kGy~15 fJNo
BrainChip AkidaSilicon Chip<100 kGy~20 fJNo

Discuss Defence Integration

Contact our defence programmes team to explore SYNAPLEX integration for radiation-hardened AI applications.

Contact Defence Team Back to SYNAPLEX Overview

Export Control Notice: Export of our products and technologies may require authorisation under UK Export Control legislation.

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