Physics + AI  ·  Elegant and Strategic

Physics-aware AI, from data center to edge.

PHYSIA trains and governs physics-informed models in a sovereign AI data center, then executes them beside your assets on FPGA — cutting repeat GPU work, uplink traffic and decision latency at once.

Physics-Informed AI+ FPGA Edge+ Sovereign AIDC = Decisions without the round trip
1,125×
Faster than solver (published edge demo)
<2 ms
Edge decision latency
4
Industry cases with unit economics
0
Third-party per-token API fees
The Platform

Industry experts shape the model.
The edge runs it. The AIDC governs it.

One delivery: process knowledge, physics-informed models, FPGA-based edge inference and sovereign AI infrastructure — with a defined control boundary for data, keys and administration.

01 / MODEL

Physics-Informed AI

A PINN fits measured data while enforcing the equations, limits and regularity your equipment must obey — an estimator, not a black box.

  • Balances data fit, physics residual, boundaries
  • Validated against reference solvers
  • Safe fallback outside the operating envelope
02 / EDGE

FPGA Edge Execution

Compact, signed models are quantized, pruned and mapped to FPGA chips beside the asset — low latency, less raw-data movement, purpose-sized hardware.

  • Repeat estimates executed locally
  • Exceptions and metrics sent upstream only
  • Custom bitstream, board & device integration
03 / GOVERN

Sovereign AIDC

A governed AI data center trains, validates, signs, monitors and distributes approved model versions — with residency, key custody and audit.

  • Open models, no third-party token fees
  • Model registry, lineage, rollback
  • Private, sovereign or hybrid deployment
How It Works

Four steps from asset to governed intelligence

01

Discover

Map the asset, process physics, failure modes and the decision worth automating.

02

Build PINN

Fit observations while enforcing equations, operating limits and regularity constraints.

03

Run at Edge

Optimize and deploy the validated PINN on FPGA for repeat local inference.

04

Govern in AIDC

Train, validate, sign, monitor and distribute approved model versions centrally.

AIDC → EDGE: signed model package   ·   EDGE → AIDC: selected metrics & exceptions
Mother Companies

Born from PINN AIDC and a strategic alliance.
One complete stack.

PA

PINN AIDC Physics-Aware AI Engine

The new-generation AI data center technology: physics-informed neural networks that reduce repeat estimation work — trained, validated and governed centrally in a sovereign AIDC, executed locally on FPGA edge accelerators. Open models, no third-party per-token fees.

AB

ABC Digital Luceor · Wireless Mesh Networks

Since 2008, Riyadh. Patented WiMESH / HyMESH mobile networking — 600 Mbps, 10 km per hop, seamless handover above 350 km/h — serving cities, governments, militaries and industry across 15+ countries, validated with stc, SAMI, NEOM, Red Sea Global and Aramco Gulf Operations.

DT

DeepTech Engineering Industrial AI Venture Builder

More than a traditional technology services provider: DeepTech develops its own AI-driven solutions, platforms and proprietary technologies for real-world industrial sectors — cybersecurity, maritime digital systems, agriculture AI, environmental intelligence and telecom sensing. By building and owning defendable IP — 50+ patents, 200+ publications — DeepTech creates scalable innovations others cannot easily replicate.

PINN AIDC + ABC Digital
× DeepTech Engineering
= PHYSIA A strategic alliance of ABC Digital and DeepTech Engineering, built on the PINN AIDC technology — connectivity from sensor to sovereign cloud, and physics-aware intelligence at every hop, delivered as one.
Industry Examples

AIDC economics, proven per use case

Illustrative unit economics on the new-generation pattern: the edge handles repeat inference, the AIDC focuses on training and complex work.

Oil & Gas · Pipeline Integrity

Detect anomalies before they become events

A PINN estimates flow state and pressure drop from local signals at a remote station, flags patterns outside the validated envelope — and keeps raw telemetry on site.

$54,000Net annual value
BREAK-EVEN
5 avoided hours / yr
Process Industry · Pump Health

Protect production uptime locally

Vibration, temperature and process load combine into an early pump-degradation estimate — prioritized maintenance routes, decided at the edge without a round trip.

$60,000Net annual value
BREAK-EVEN
28 avoided hours / yr
Additive Manufacturing · Thermal State

Consistency in every build layer

A thermal PINN estimates process state between direct measurements, flagging zones associated with rework or rejection before the build is lost.

$30,000Net annual value
BREAK-EVEN
40 builds / yr
Fleet & Logistics · Availability

Vehicle condition, decided at the edge

Load, temperature, vibration and duty-cycle context produce a local condition estimate — service scheduling that keeps working even with weak connectivity.

$35,000Net annual value
BREAK-EVEN
223 vehicle-days / yr
Partners & Clients

Validated by industry. Trusted by governments.

A selection of partners and clients across the three mother companies — from European industry and Saudi giga-projects to global institutions.

stc
SAMI
NEOM
Red Sea Global
AIRBUS
Abu Dhabi Ports
Kongsberg
Cricketone
UNODC
World Bank
NAVAL Group
DP World
Co-Founders

Leadership with intellect, creativity and purpose.

Dr. Hanan Althubetee
Co-Founder

Dr. Hanan Althubetee

A distinguished Saudi entrepreneur and legal expert, Dr. Althubetee holds a PhD in Law and brings over 15 years of experience in the banking and real estate sectors. She is the founder and owner of several companies operating in technology, construction, and professional services. An active member of the Orphans Association and a passionate admirer of art and fashion, Dr. Hanan represents the new generation of visionary Saudi women leading with intellect, creativity, and purpose.

dr.hanan@phy-sia.com
Dr. Hosni Emam
Co-Founder

Dr. Hosni Emam

A seasoned Chief Business Officer with a PhD in Explainable Artificial Intelligence and Human-in-the-Loop: A Framework for Trustworthy, Transparent, and Accountable Systems, MBA, with a wealth of experience in venture capital and private equity. His expertise spans digital payments, cryptocurrency, and the Food & Beverage industry. Emam holds a Law degree and is a licensed high court lawyer across the Arab world, as well as a member of Arab Lawyer Associations. Renowned for his legal acumen, he serves as a trusted advisor and intermediary for international companies, leveraging his skills in international commercial arbitration, diplomatic relations, and conflict resolution. His meticulous market analyses and extensive networks make him a sought-after strategist for global brand expansion.

dr.hosni@phy-sia.com
Measured Pilot

Prove it on one repeated decision before you scale.

We benchmark the physics-aware edge architecture against your current baseline on the same workload — model error, GPU-hours, energy, and end-to-end unit economics.

dr.hanan@phy-sia.com dr.hosni@phy-sia.com Riyadh · Saudi Arabia