Haiqu Demonstrates Improved Anomaly Detection And Pattern Recognition with IBM Quantum Computer 

Insider Brief

• Haiqu has demonstrated that current quantum computers can detect anomalies in complex datasets more efficiently than classical systems, showing early signs that quantum machine learning may soon deliver real-world advantage.
• The company used IBM’s Quantum Heron processor to encode over 500 features across 128 qubits, enabling faster preprocessing and improved accuracy in financial anomaly detection compared to classical baselines.
• Haiqu’s proprietary quantum embedding technique allows large-scale data to be compactly represented on today’s quantum hardware, potentially accelerating applications in finance, healthcare, and environmental monitoring.

PRESS RELEASE — Haiqu, an emerging quantum software company, has demonstrated that today’s quantum computers could detect anomalies more efficiently than classical systems in classification problems across finance, healthcare, weather and more.  

The work, run over the cloud on an IBM…