Editorial Standards

Independent Research. Analytical Intelligence.

Physical AI Journal is an independent research publication focused on humanoid robotics, physical AI systems, industrial automation, and the commercial and operational dynamics of robotics deployment.

Our editorial standards are designed to ensure that all published content meets the requirements of accuracy, transparency, consistency, and professional integrity expected by operations leaders, automation buyers, integrators, investors, and industry stakeholders.

Our objective is to provide reliable, independent intelligence that helps readers evaluate platform capability, deployment economics, and adoption decisions in the physical AI and humanoid robotics sector.

Editorial Principles

All content published by Physical AI Journal is guided by five core principles:

Accuracy
We strive to ensure that factual statements, technical specifications, pricing figures, and deployment claims are verified against authoritative or primary sources before publication. Where a figure originates from a manufacturer or vendor and cannot be independently corroborated, it is explicitly labelled as company-claimed.
Transparency
We aim to clearly distinguish between verified fact, vendor-claimed information, market data, analytical interpretation, and forward-looking observation. Estimates and projections are identified as such and are never presented as confirmed figures.
Relevance
Research and analysis are selected based on their practical importance to organisations evaluating physical AI adoption, platform selection, or capital allocation decisions.
Independence
Editorial decisions are made independently and are not influenced by advertisers, sponsors, robotics manufacturers, integrators, or other commercial partners. No published analysis is developed in exchange for platform access, promotional consideration, or commercial arrangement.
Clarity
Complex technical and commercial developments are translated into clear, accessible language while maintaining factual precision and professional standards.

Source Validation Process

Physical AI Journal prioritizes authoritative and publicly available sources when developing articles, intelligence briefings, and research reports.

Primary sources may include:

Company filings, investor disclosures, and regulatory filings (e.g. SEC)
Official manufacturer specification sheets and pricing documentation
International Federation of Robotics (IFR)
IEEE Spectrum
Silicon Valley Robotics Center
Recognised market intelligence and analyst research (referenced and attributed, not reproduced)
Verified news reporting from established trade and business media

Where a claim originates solely from a manufacturer, vendor, or promotional source and cannot be independently verified, it will be identified as company-claimed and will not be presented as an established fact.

Where deployment, performance, or outcome information cannot be independently verified through authoritative sources, it will not be presented as confirmed fact.

AI-Assisted Research and Editorial Oversight

Physical AI Journal uses advanced artificial intelligence technologies to support research, source discovery, document analysis, trend monitoring, and information synthesis.

AI tools assist in identifying relevant developments, comparing multiple sources, structuring research findings, and accelerating analytical workflows. AI-generated outputs are not published automatically.

All published content is subject to editorial review and human oversight before publication. The use of AI enables faster research and broader source coverage while maintaining editorial accountability and quality control.

Corrections Policy

We are committed to maintaining accurate and current information, in a sector where platform specifications, pricing, and deployment status change frequently.

If a factual error, outdated figure, broken reference, or material omission is identified, we will review the matter and make corrections where appropriate. Significant corrections may be accompanied by an editorial update note to maintain transparency.

Readers who believe content may contain an error are encouraged to contact us through our Contact page.

Scope and Regulatory Disclaimer

Physical AI Journal provides research, analysis, and educational information for informational purposes only.

Content published on this website does not constitute legal, financial, investment, engineering, safety-certification, or professional advice of any kind. Physical AI Journal does not evaluate, certify, or endorse the safety, technical conformity, or fitness-for-purpose of any specific robotic platform or deployment.

Readers should obtain independent professional, technical, and legal advice before making procurement, deployment, safety-certification, or investment decisions.

Editorial Contact

Questions regarding editorial standards, corrections, or published content can be submitted through our Contact page.

Physical AI Journal is a digital publication and research platform operated by Sekason Research Limited, London, United Kingdom.

Company Registration Number: 14339910
London, United Kingdom
Email: contact@sekasonresearch.com
Website: https://www.physicalaijournal.org