Applied researchfor federalprograms.
Twelve years building what the Department of Defense and the Department of Energy ask for and cannot buy. Machine learning, cybersecurity, hyperspectral imaging, synthetic aperture radar, signal processing, metamaterials and hypersonics.
- Track record
- Twelve years · thirteen federal awards
- Agencies
- Navy · Air Force · DARPA · MDA · DHS · DOE
- Partners
- Lockheed Martin · Penn State · Idaho National Lab
- Vetting
- DCAA audited · HubZone · DOT and State of California
CyberNeuro-RT
Real-time network defense built on a hybrid supervised and unsupervised deep learning engine. The same models deploy on CPU, GPU or low-power neuromorphic chips, so detection runs in a cloud core or on a sensor at the edge.
CyberNeuro-RT is a second layer of defense. It runs alongside the perimeter tools already in place and is built to reduce the likelihood of an intrusion succeeding, and to surface the ones that do sooner. No security product prevents every attack, and we do not claim otherwise.
HPC-scale intrusion detection
Detects intrusions across high-performance computing networks with unparalleled efficiency.
Comprehensive attack coverage
Supports detection of known attack types including DoS, DDoS and ransomware.
Flexible deployment
Deployable across edge, hybrid or full cloud infrastructure to meet your needs.
Hybrid deep learning
Combines supervised and unsupervised deep learning for robust threat identification.
Dynamic AI model management
Real-time model updates and continuous retraining for evolving threats.
Intuitive security dashboards
Interactive dashboards provide clear insights for efficient security operations.
Three products, out of the federal programs behind them.
One product line, from real-time network defense through to source code.
CyberNeuro-RT
Real-time network intrusion detection on a hybrid supervised and unsupervised deep learning engine, deployable on CPU, GPU or neuromorphic silicon.
Read more →
CNRT Vanguard
Automated HPC-scale network anomaly monitoring and autonomous threat mitigation.
Read more →
CNRT CodeLens
AI-driven source code vulnerability detection, trained on mission-critical repositories.
Read more →Thirteen federal programs, twelve years.
Major programs running with the Navy, the Air Force, DARPA, the Missile Defense Agency, Homeland Security and the Department of Energy, alongside Lockheed Martin and the national laboratories.
SBIR II · TRL 5 Real-time synthetic aperture radar simulator Synopsis +
A simulator that generates synthetic aperture radar imagery in real time, so detection and classification models can be trained and evaluated against scenarios that are impractical or too expensive to fly.
Lockheed Martin · Dr. Andrew Willis
SBIR · TRL 4 Source-code vulnerability detection Synopsis +
Static and learned analysis of source repositories to surface exploitable defects before code ships, trained against mission-critical codebases. Commercialised as CNRT CodeLens.
Lockheed Martin · U. Wisconsin–Madison
SBIR · TRL 3–4 Hyperspectral image detection of UAVs Synopsis +
Detects and classifies small uncrewed aircraft from hyperspectral imagery, using spectral signature rather than shape, so targets that defeat conventional optical tracking are still resolved.
Lockheed Martin · Bodkin Design
SBIR · TRL 3 Metamaterial-enhanced micromirror surfaces for infrared beam control Synopsis +
Engineered metamaterial surfaces on micromirror arrays that steer and shape infrared beams without moving bulk optics, reducing the size, weight and power of the assembly.
Duke University
SBIR · TRL 3 Smart image-recognition sensor using metamaterial optics Synopsis +
A sensor that performs part of the recognition task in the optics themselves, using metamaterial elements, so less computation is required downstream of the focal plane.
Lockheed Martin
SBIR · TRL 3 Next-generation toolsets for weapons separation evaluation Synopsis +
Modelling tools for evaluating store separation from an aircraft, replacing part of a test campaign that is otherwise flown.
Dr. Raktim Bhattacharya
SBIR · TRL 3 ML database for low-flammability polymer matrix composites Synopsis +
A curated database and learned models relating composite formulation to flammability, so candidate materials can be screened before they are manufactured and burned.
Richard E. Lyon
STTR II-A · TRL 6 Electrochemical recycling of electronic constituents of value Synopsis +
Recovers gold, copper and other constituents of value from electronic waste electrochemically and at room temperature. 25% higher recovery, 75% less chemical reagent, 30% lower water and electrical cost, and no toxic emissions. Commercialised as E-RECOV.
Idaho National Lab · Colt Refining
SBIR II · TRL 4 HPC-scale cyber-threat detection using neuromorphic processing Synopsis +
The programme CyberNeuro-RT came out of. A hybrid supervised and unsupervised deep learning ensemble for network intrusion detection, ported to neuromorphic silicon so inference runs at a fraction of the power a GPU needs.
Pennsylvania State University
SBIR · TRL 3 AI/ML verification and validation Synopsis +
Methods for establishing that a trained model behaves within specification before it is fielded, addressing the assurance gap that keeps machine learning out of safety-critical defence systems.
North Carolina State University
STTR · TRL 3 Ground-based hypersonic threat detection using neuromorphic processing Synopsis +
Detection and tracking of hypersonic threats from ground-based sensors, with inference on neuromorphic hardware to hold the latency budget that the closing speeds demand.
Lockheed Martin · University of Florida
SBIR · TRL 3 Contraband detection using hyperspectral imaging and neuromorphic processing Synopsis +
Identifies concealed contraband by spectral signature at ports of entry, with on-sensor neuromorphic inference so screening runs at the speed of the queue.
Lockheed Martin · Bodkin Design
SBIR · TRL 3 Multi-sensor object detection and tracking Synopsis +
Fuses several dissimilar sensors into a single track picture, holding identity across handoffs where any individual sensor loses the object.
Dr. Raktim Bhattacharya
An AI research company, across seven fields.
Federal program offices bring us problems that have no answer yet. The work spans radar and signal processing, machine learning, cybersecurity and materials — find an answer, then engineer it into something that survives contact with the real world. In government work you cannot be a single-focused company.
Five offices, three continents.
A multifaceted operation. In government work you cannot be a single-focused company.
San Jose, California
Quantum Ventura Inc.
Carson City, Nevada
Operations
Dubai, U.A.E.
Quantum Guru · Unit R40, Burjuman
Tokyo, Japan
Distribution and support
Vancouver, British Columbia
Engineering
Consortiums and certifications.
Tell us the program
and the problem.
We reply from San Jose, usually within two working days.