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DEFENSE & ENERGY DISASTER RESPONSE

How It Works

From raw, messy field data to a deployed model on tactical hardware — four stages, fully auditable.

Jaxorik AI pipeline: Raw Data to Deployment Four-stage pipeline showing how Jaxorik transforms messy field data into deployed AI models: Raw Data, Auditable Model, Quality Assurance, Deployment. Below: three differentiators — built for broken data, designed by veterans, compliant by design. 1. Raw data Messy, noisy, incomplete, or classified inputs Satellite imagery Field comms Infrastructure maps 2. Auditable model Custom, explainable AI with full decision audit trails No black boxes 3. Quality assurance Validated under extreme conditions DoD-standard compliance 4. Deployment Field-ready on tactical hardware Runs offline Model updates, patches Built for broken data Standard models require corrupted samples to be omitted. Ours don't. Designed by veterans Built by engineers with firsthand SIGINT field data experience Compliant by design Export-control aware, DoD-standard QA, never black-box

Technical Philosophy

Most AI vendors assume your data is clean, structured, and complete. Real field conditions don't cooperate with that. In defense and disaster response, that gap can cost lives.

Jaxorik builds auditable models designed by engineers with firsthand experience collecting and interpreting signals intelligence in the field — where data is incomplete, noisy, and mission-critical. We believe humans are decision-makers; AI is a tool that supports them.

Input to Black Box to Output - This is Bad Science

Every Jaxorik model is explainable, auditable, and deployable in austere environments where cloud-based AI fails.

Built for Messy, Chaotic Data

Traditional AI models assume clean, complete, structured inputs. Real-world field data rarely cooperates with that. Our models are designed to handle:

Corrupted Imagery

Satellite or drone feeds with cloud cover, compression artifacts, partial occlusion, or missing frames.

Dropped Sensor Feeds

Signals that drop out, spike, arrive out of sequence, or go silent entirely during a mission.

Incomplete Records

Datasets with missing fields, corrupted entries, or conflicting sources — common in crisis conditions.

Real Example: LIGO Gravity Spy Dataset

Gravity Spy spectrogram samples showing corrupted and noisy data including solid green squares representing missing or corrupted samples

Real gravitational wave detector data used in Jaxorik's research. The solid green squares are corrupted or missing samples. Since a standard model requires clean data, it would omit the corrupted samples — training your AI to ignore the exact conditions it will face in a crisis.

Our approach maintains classification performance even when inputs are incomplete, handling these gracefully rather than generating false confidence.

Where a standard model hallucinates or crashes, ours degrades gracefully — flagging uncertainty instead of generating false confidence.
Download Capabilities Statement

Company Standards

Jaxorik operates under strict ethical guidelines, maintaining export-control awareness as standard practice and adapting to client-specific compliance requirements.

Security Standards

Export-control awareness, air-gapped data handling, adaptable to client compliance requirements.

Quality Assurance

Transparent methodologies, auditable algorithms, reproducible results.

Mission Focus

National security priorities, decision-support systems — never autonomous weapons.

About the Founder

Rae Chipera
PhD Candidate, MBA | Founder & CEO

Data scientist with extensive military and industry experience building novel AI solutions for national defense applications.

PhD candidate in Data Science at National University, with an MBA in Quantitative Finance. Former Marine SIGINT Analyst and firsthand understanding of the operational constraints faced by defense and intelligence organizations.

Rae Chipera, Founder & CEO of Jaxorik AI Research Group
Rae Chipera — Founder & CEO

Military Service

Rae served in the United States Marine Corps as a Signals Intelligence Analyst, including deployment to Iraq in support of Operation Iraqi Freedom.

Her military experience provides unique insight into the operational requirements and constraints faced by defense and intelligence organizations deploying AI systems in challenging environments.

Service Highlights

  • Iraq Campaign Medal — Combat deployment
  • Good Conduct Medal — Exemplary service
  • Expert Rifle Badge — Almost perfect score (249/250)
  • Expert Pistol Badge
  • Held a TS/SCI Security Clearance
Rae Chipera in USMC uniform
Cpl. Chipera, USMC

Education & Expertise

Academic Background

  • PhD Candidate, Data Science — National University
  • MBA in Quantitative Finance
  • MIT & CMU professional ML/Deep Learning programs
  • Los Alamos, NM native

Technical Expertise

  • Explainable AI Systems
  • Reservoir Computing & Echo State Networks
  • Edge & Offline Deployment
  • Export-Control Compliance
  • Disaster Response & Search and Rescue

Contracting Credentials

  • UEI: K8ENCCGZ2M13
  • CAGE: 11X70
  • WOSB Certified
  • SDVOSB Certified
  • Listed in SAM.gov Disaster Response Registry

Head of Document Shredding

Ghost Rider, Jaxorik Head of Document Shredding, a Carolina Dog

Responsible for secure disposal of sensitive materials and maintaining office morale. Expert in paper destruction and treat negotiation.