Press release
Paul George Savluc: The Engineer Connecting AI, Robotics, Industry, and Health at Internet Scale
Paul started from nothing, graduating with a bachelor's at the age of 19, while working multiple jobs at once. He inspired, trained and mentored over 3000 engineers over the past 2-3 years. He even is on the official verified credits section for the Mandalorian Season 3.
As can be verified here: The Mandalorian Chapter 23: The Spies (TV Episode 2023) - Full cast & crew - IMDb
He's building a pipeline of outcomes: AI systems that ship, engineering platforms that accelerate real hardware, and business development networks that move deals across borders. Add to that a serious push into medical technology and non-intrusive sensing, and you get a profile that's increasingly rare: a founder-operator who can speak software, hardware, data, and deployment without turning it into vaporware.
What makes Paul unusually visible is not just the work, it's the distribution. His network is being grown with a media and partnership strategy designed to amplify technical and business content at scale. Based on internal projections tied to current growth and publishing cadence, the network is targeting 7M+ views in 2025 and 100M+ views in 2026. Those are forecasts, not guarantees, but the direction is clear: Paul is building the kind of reach that turns engineering into a global conversation and turns conversations into contracts.
A business development network built like a system
Most "networking" is chaos. Paul's approach is closer to an engineered system: repeatable, measurable, and designed for compounding.
He's been developing a business development engine that connects:
o organizations who need credible technical leadership in public.
o companies who need product acceleration and data systems,
o founders and engineers who need build capacity,
The point is not hype. The point is high-trust distribution: producing content, demos, technical breakdowns, and partnership outreach that makes it easier for serious organizations to say yes, faster.
Engineering and AI: from ideas to working systems
Paul's technical work clusters around applied AI infrastructure and generative engineering:
o Prioritizing simulation and digital-twin thinking, because the cheapest prototype is the one you can break in software before you break it in the real world.
o Developing workflows for generative AI in electronics and embedded systems, where constraints are real and mistakes are expensive.
o Building LLM and NLP pipelines that are designed for production constraints, not demos.
That mindset shows up in his platform work at OpenQQuantify and in analytics and automation efforts across business systems.
The medical and health-tech side: non-intrusive sensing and practical diagnostics
Paul's medical-side work focuses on engineering realities that matter: signal quality, usability, privacy, and deployment.
His interests and efforts include:
o Building health-tech concepts that lean toward real utility: better monitoring, better data capture, better interpretation, and better integration into systems people already use.
o Non-intrusive sensing for monitoring physiological signals using modalities like EEG-adjacent approaches, acoustics, and other sensor pathways.
o Online AI Medical Diagnostics
o A worldwide medical platform for people to talk to online doctors and book specialized medical help.
This is not "health content." It's engineering applied to human outcomes, where safety, accuracy, and reliability are the whole game.
Why companies hire and contract Paul
Organizations bring Paul in when they need someone who can operate across layers:
o partnership and deal motion
o product delivery and systems architecture
o electronics and embedded constraints
o AI engineering + infrastructure
He's built to be a multiplier: capable of building directly, but also capable of shaping roadmaps, teams, and execution that survives reality.
What Paul is actively open to worldwide
Paul is a strong fit for global roles and contracts in:
o Technical product leadership and founder-level execution
o Health-tech sensing and signal-driven system design
o Embedded and edge systems with AI integration
o Robotics
o AI + simulation and digital-twin engineering
o MLOps and ML systems engineering (pipelines, monitoring, data quality, deployment)
o Applied LLM systems (RAG, tool use, retrieval, evaluation, latency work)
o Business Development (Digital and Physical)
Paul is building compounding distribution around real engineering output, and that combination tends to scale fast when it's consistent.
Cybersecurity and government compliance automation: making regulation executable
Savluc's published work highlights a practical theme: compliance is not just policy, it's an operational system. His books focus on turning U.S. Government contracting and cybersecurity requirements into repeatable engineering workflows, bridging controls, audit-readiness, incident response expectations, and systems automation.
His current Amazon Kindle titles include:
Amazon.com: The US Government Compliance Automation Handbook: How to Work with the US Government : From FAR and DFARS to Cybersecurity, Privacy, Labor, Exports, Audit Survival, and Systems Automation with Python
Amazon.com: Comprehensive Guide for Defense and US-Government Cybersecurity & Contracting Compliance: Compliance Guide: FAR/DFARS, CMMC, NIST 800-171, Incident Response, ITAR/EAR, and Post-Quantum Cryptography
Amazon.com: The DoD CMMC Program: A Comprehensive Analysis & How to Comply: An Explanation of the DoD CMMC Program & Cybersecurity Regulations
Contact Details
Organization: OpenQQuantify
Contact Person: Paul Savluc
Website: https://www.openqquantify.com
Email: Send Email [https://dashboard.kingnewswire.com/release-contact/34899]
Contact Number: +40751476842
Address: 560 Raven Woods Drive, suite 215
Address 2: suite 215
City: North Vancouver
State: BC
Country: Canada
Release Id: 17122534899
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