The real quantum advantage starts with getting involved now

We combine AI, knowledge engineering and quantum computing research to solve complex business and scientific problems.

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About Qnow

Qnow is a deep-tech company focused on knowledge generation, knowledge mining and intelligent systems.

We combine artificial intelligence, knowledge engineering and quantum computing to help organizations extract value from complex information, accelerate research and build new technological capabilities.

Our work spans AI systems, knowledge graphs, autonomous agents, quantum machine learning and applied R&D, connecting research with real-world applications.

Industries

Financial

Transforming complex financial data into actionable intelligence through AI and knowledge systems.

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Bio / Chemical / Healthcare

Accelerating drug discovery and molecular research through AI, QSAR, and quantum computing.

Explore our products

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Construct

Semantic canvas for designing agentic systems. Connect nodes, validate the architecture and compile 5 ready-to-ship Markdown artifacts — brief, spec, backlog, eval, ops.

Doekit

Design of Experiments (DoE) in Python — screening, response surface, optimal design, and an agentic evaluation layer.

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Complexometrum

Complexometrum measures dataset complexity to assess trainability and guide better modeling decisions.

Ungraph

Transforms unstructured documents into structured Lexical Graphs, enabling advanced information retrieval.

Our services

From research to real-world applications, we build intelligent solutions around complex data and emerging technologies.

AI & Knowledge Systems

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Build AI agents, knowledge graphs, RAG systems, and intelligent workflows that turn complex information into actionable insights.

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Quantum R&D

Explore and develop quantum and hybrid solutions for real-world problems, from algorithm research to QML and quantum experimentation.

Extend your R&D capabilities with specialized research, prototyping, experimentation, and technical validation across AI and quantum computing.

Applied Research & Innovation

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— Publications

Research & Breakthroughs

Quantum QSAR for drug discovery

Q2SAR: A Quantum Multiple Kernel Learning Approach for Drug Discovery

Initial research direction using quantum support vector machines.

Alejandro Giraldo, Daniel Ruiz, Mariano Caruso, Javier Mancilla, Guido Bellomo.

May 2025

A multiple-kernel approach evaluated on DYRK1A inhibitor classification.

Alejandro Giraldo, Daniel Ruiz, Mariano Caruso, Guido Bellomo.

June 2025

Q²SAR: Overcoming Classical Bottlenecks in Drug Discovery

The newer publication reports an AUC of 0.8750 against 0.8037 for its Gradient Boosting benchmark. These are reported experimental results, not evidence of a general quantum advantage across drug discovery.

Alejandro Giraldo, Daniel Ruiz, Mariano Caruso, Guido Bellomo

July 2026

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Ecosystem & Technology Partners

Qnow's partners

Get in Touch

Discuss Research & Integrations

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• Learn more about our research and tools.
• Explore academic or industry partnerships.
• Discuss potential use cases or integrations.

info@qnow.tech