QHANTOM TECH

Rethinking personal computing for the AI age

Qhantom Tech is exploring a trust-first, post-app personal computing platform that rethinks how humans interact with artificial intelligence at the system level through hardware and architecture. Early-stage research and prototyping focused on human–AI interaction, computing architecture, and trust boundaries.

THE PROBLEM

Artificial intelligence is becoming embedded into everyday life, yet the interfaces used to interact with it are still built around app-based and engagement-driven software models.

  • App-centric systems were not designed for autonomous intelligence
  • Trust and control are delegated to software settings rather than architecture
  • Users lack clear boundaries, intent, and visibility in AI interactions

As AI becomes ambient, these limitations become structural problems rather than interface issues.

THE IDEA

Qhantom Tech is prototyping a personal trust node, a dedicated computing system that sits between the user and AI systems.

Instead of relying on apps, Qhantom explores system-level interaction where intent, permissions, and boundaries are enforced by the architecture itself rather than by individual applications.

At its core, the work is motivated by the question of how AI systems can be designed to respect human intent, limits, and behavior rather than reshaping human behavior to fit software.

System architecture reference:

User
Trust Node
AI Systems
Output

WHY HARDWARE

Software-only AI interfaces optimize for convenience and engagement. Hardware allows enforceable constraints.

By designing the computing environment itself, Qhantom explores how trust, agency, and clarity can be restored through physical systems rather than abstract software controls.

Grounding AI interaction in physical computing systems allows human constraints, intuition, and agency to shape the technology rather than the reverse.

CURRENT STAGE

Qhantom Tech is in an early, exploratory phase.

  • Physical prototype development underway
  • OS and system-level interface experiments in progress
  • Research-driven approach focused on feasibility and learning

These experiments are intended to evaluate feasibility, constraints, and interaction tradeoffs before product definition.

TEAM

Dylan Morris-Gray

Founder

System architecture, hardware prototyping, human–AI interaction design

Muhammad Waqas

Full Stack Engineer

Software implementation, system prototyping, interface experimentation

SYSTEM: ONLINE//NEXT DROP: SUMMER 2026//QTM SUPPLY: 1B//SECTOR: FASHION LAB ACTIVE//LAUNCH: SUMMER 2026//STATUS: PRE-LAUNCH//
SYSTEM: ONLINE//NEXT DROP: SUMMER 2026//QTM SUPPLY: 1B//SECTOR: FASHION LAB ACTIVE//LAUNCH: SUMMER 2026//STATUS: PRE-LAUNCH//
SYSTEM: ONLINE//NEXT DROP: SUMMER 2026//QTM SUPPLY: 1B//SECTOR: FASHION LAB ACTIVE//LAUNCH: SUMMER 2026//STATUS: PRE-LAUNCH//