QGI (Quantum General Intelligence) introduces quantum algorithm engine for real-world production AI systems

Machine Learning


QGI positions the QAG engine as the foundational infrastructure, the inference layer of AI systems that goes beyond search and toward deterministic decisions.

Quantum General Intelligence, Inc. (QGI) today announced Q-Prime, a quantum structure embedding model, and introduced a public preview of QAG Engine (Quantum Augmented Generation), a quantum algorithm-powered inference system designed for real-world enterprise AI applications that require accuracy, traceability, and control.

We are not waiting for quantum computers. It is the first practical quantum embedding model running on GPU infrastructure to infer complex, structured knowledge for enterprise buyers. ”

— Dr. Sam Saman

Quantum algorithms applied to enterprise AI

QGI brings quantum algorithms into production by applying the mathematical framework of quantum mechanics, such as Hilbert space representations, superposition, and interference, to classical GPU infrastructure.

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Unlike experimental quantum hardware systems, QAG currently runs on NVIDIA GPUs, enabling immediate deployment across enterprise workloads.

From search to inference in real applications

Traditional AI systems rely on search augmentation generation (RAG), which creates limitations in real-world scenarios due to the following reasons:

Chunking fragmented documents
incomplete search
hidden contradiction
lack of verifiable inferences

QAG engines replace search-centric pipelines with inference-first approaches based on quantum structure representations and deterministic signal processing.

quantum structure inference engine

At the core of QAG is Q-Prime, which encodes enterprise data into a quantum structured hypergraph that preserves relationships and dependencies lost in traditional embeddings.

This structure is processed through QGI’s Hilbert Space Compression (HSC) layer to produce an interpretable inference signal.

conflict
dependence
coverage
consistency
redundancy
topology

These signals allow AI systems to infer complex knowledge before producing output.

Real applications across enterprise systems

The QAG engine is designed for immediate use in real-world environments such as:

Financial services — underwriting, risk assessment, compliance
Healthcare — clinical decision support, structured medical reasoning
Legal system — policy analysis, contract reasoning
Regulatory Affairs—Audit, Reporting, and Enforcement Workflows
Enterprise AI systems — knowledge platforms and decision engines

Additional applications include:

Persistent memory for AI agents
Long context inference in enterprise workflows
Multi-agent coordination and decision orchestration

Not just a model, but an engine

QGI positions the QAG Engine as the core infrastructure for enterprise AI systems, delivering:

Structured reasoning for corporate knowledge
Deterministic signal generation for decision support
Traceable and auditable inferences
Versioned knowledge and reproducible output

“We are now applying quantum algorithms to real-world enterprise systems,” said Dr. Sam Sammane, CTO and Founder of QGI.
“The QAG engine is designed to move AI from probabilistic output to structured, reliable inference.”

Deploying to classic infrastructure

Q-Prime and QAG run on classical GPU systems using NVIDIA CUDA-Q and cuTensorNet, delivering interactive performance without the need for quantum hardware.

Also read: The infrastructure war behind the AI ​​boom

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