Real-World Data,

Verified for AI

Paired gives healthcare systems the confidence to innovate without compromising patient trust.

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Our Purpose

Give healthcare systems the ability to use their own data safely, accurately, and ethically.

Our
Vision

We’re building a future where clinical truth is verifiable, insights are grounded in reality, and AI is accountable.

What Makes Us Different

Paired is built for real clinical environments: privacy-first, identity-free, and fully aligned with global and UAE health regulations.

Our Approach

Healthcare comes first but our architecture is universal. The same verification layer that strengthens hospitals today will support autonomous systems, smart cities, and human-machine intelligence tomorrow.

The Team

Raluca Cherciu

Co-Founder & Board President

Aleks Kay

Co-Founder & CSO

Omar Peracha

Co-Founder & CTO

Prof. Dr. G. Schwabe

Advisor

Prof. of Information Management,
Data Driven Models,
Blockchain Enhanced Trust,
Health-Records, University of Zurich

Gustavo Mana, PhD

Advisor

Advanced Data Center Solutions, Blockfusion

Prof. Dr. Paul J. Zak

Advisor

Prof. of Economic Sciences & Psychology, Management Director, Claremont Graduate University

Prof. Dr. C. J. Tessone

Advisor

Prof. of Blockchain & DLTs,
Chairman of Blockchain Center,
University of Zurich

Ralf Glabischnig

Board Member

Inacta Ventures

Dr. Andreas Glarner

Advisor

Legal Partner at MME, Attorney at Law, LL.M FinTech

It’s not too late to improve

See how verified, real-world data can transform care, operations, and AI accuracy inside your institution.

Get Started

Blog Articles

The Knowledge Hub

See All

Privacy Preserving Health Data Infrastructure: Compliance and Collaboration

National healthcare systems are rapidly building digital exchanges and integrated data platforms.

From Big Data to Verified Reality: Why Healthcare AI Needs Real-World Interactions

Healthcare systems today generate enormous volumes of data from electronic records, registries, sensors, and administrative platforms.

Cryptographic Lineage for Clinical AI: Meeting the Demands of a High Risk Domain

As AI tools enter clinical environments, regulators, health systems, and scientific communities increasingly require transparency and accountability.

Real-World Data,

Verified for AI

Our Purpose

OurVision

What Makes Us Different

Our Approach

Raluca Cherciu

Aleks Kay

Omar Peracha

Prof. Dr. G. Schwabe

Gustavo Mana, PhD

Prof. Dr. Paul J. Zak

Prof. Dr. C. J. Tessone

Ralf Glabischnig

Dr. Andreas Glarner

It’s not too late to improve

The Knowledge Hub

Our
Vision