Technology | Quantum Links AI - How Intelligent Routing Works
The Intelligent Routing Engine
At the heart of Quantum Links AI is a sophisticated, data-driven routing engine. It leverages a vast library of pre-built benchmarks to create a performance map that predicts the time, cost, and energy consumption of a given task on different hardware. This allows the system to make a sub-second decision on whether a quantum advantage is achievable and routes the workload accordingly.
Our platform moves beyond simplistic, rule-based routing to a dynamic, predictive model that learns and improves over time. It is an autonomous, self-learning engine that intelligently routes computational problems to the optimal resource—classical or quantum—in real time.
A Robust, Production-Ready Foundation
Current Status: Phase 2 Complete – Hardware Integration Active
Codebase: 33,000+ lines of production-quality Python code
Quantum Frameworks: Cirq, PennyLane, Qiskit
Hardware Integrations: AWS Braket SDK, IBM Quantum Platform
Simulated QPU Profiles: High-fidelity digital twins of IonQ and IBM hardware using realistic noise parameters
Classical Frameworks: PyTorch, TensorFlow
Architecture: A modular, API-driven architecture designed for scalability and the seamless integration of new hardware and frameworks.
From Validation to Customer Value
Phase 1: Foundation (Complete)
Built and validated the core orchestration engine, demonstrating 72%+ routing accuracy across 20+ diverse computational benchmarks in a simulated environment.
Phase 2: Hardware Integration (Complete)
Developed the adaptive routing engine and successfully integrated with the AWS Braket SDK and IBM Quantum Platform. The platform can now communicate directly with physical quantum computers, query their status, and is ready to submit jobs.
Phase 3: Real Hardware Execution (In Progress)
Executing our first benchmark workflows on real quantum hardware. This phase focuses on running the VQE algorithm for Molecular Hydrogen (H₂) on a real QPU (IonQ Forte 1 via AWS Braket) to demonstrate tangible quantum advantage and validate our cost-saving claims.
Phase 4: Industry Problem Expansion (Upcoming)
Implementing additional industry-relevant problems, including Portfolio Optimisation (Fintech) and Vehicle Routing (Supply Chain), to demonstrate the platform’s broad commercial applicability before launching customer pilots.