AI Lab itinai.com

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Editorial Policy itinai.com

At itinai.com, we take editorial integrity seriously. Our mission is to create trustworthy, useful, and verifiable content in the field of artificial intelligence, innovation, and product development.

Every article published on itinai.com undergoes human review and aligns with the principles below.

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Our Editorial Principles

  • Accuracy – We fact-check our content and update it when necessary.
  • Transparency – We disclose the source, author, and publishing intent.
  • Experience-first – Our content is written or reviewed by practitioners and domain experts.
  • Human in the loop – No article is published without human editorial oversight.
  • Clarity – We prioritize plain, accessible language and practical insight.
  • Accountability – Errors are corrected. Feedback is encouraged and valued.

Submit a Correction or Suggest an Update

We welcome suggestions to improve our content.
If you’ve spotted a factual error, an outdated reference, or wish to propose an edit:

📬 Email: editor@itinai.com

All valid correction requests are reviewed within 72 hours.
In most cases, you will receive a reply from our editorial team.

Submit a News Item or Contribute Content

Want to submit a story, research highlight, or industry insight?
We accept contributions in the following formats:

  • Short AI news (100–300 words)
  • Research summary (with link to paper)
  • Opinion/editorial piece
  • Product case study (original only)

📥 Send your pitch to: editor@itinai.com
💡 Guest authorship is available — we credit all contributors.

Editor-in-Chief assistant

We strive for accuracy and relevance in all our publications. If you’ve found an error, outdated information, or misinterpretation — we want to hear from you. Itinai.com accepts news tips, summaries, original opinion pieces, and product stories in the field of AI, machine learning, and digital innovation.

Editorial Review Process

Every piece of content published on itinai.com follows a structured editorial workflow:

  1. Drafting – Written by in-house authors or external contributors.
  2. Expert Review – Reviewed by a domain specialist (AI, product, healthcare, or law).
  3. Editor-in-Chief Review – Final oversight by Vladimir Dyachkov, Ph.D.
  4. Fact-Checking – Sources verified manually and/or via LLM-assisted tools.
  5. Markup – Structured data (Article, Person, WebPage) is applied.
  6. Publishing – With author attribution and publishing date.
  7. Monitoring – Regularly re-evaluated for accuracy and relevancy.

Note: If AI tools assist in drafting or summarizing, this is clearly disclosed.

User & Company Feedback, Corrections

We actively encourage users, companies, and institutions to report factual errors or request content updates.

How we handle it:

  • Submissions are received
  • An editor reviews the case manually within 72 hours.
  • Verified changes are fact-checked again, optionally using AI models for cross-verification (e.g., citation match, entity comparison).
  • If the correction significantly changes the context or outcome, we:
  • Add a “Corrected on” notice to the article
  • Publish a separate editorial blog post explaining the change in our Editor’s Blog

We do not silently alter content unless it’s a typo or formatting issue.

Propose a Story or Suggest an Edit

We believe in collaborative knowledge. Anyone can contribute insights or highlight gaps.

📬 To contribute:

We welcome:

  • Original insights
  • AI research summaries
  • Localization use cases
  • Startup/product case studies

Every submission is reviewed by humans. We may edit for clarity or add editorial context.

Get Involved

Follow us, contribute insights, or propose partnerships. We welcome collaboration from researchers, writers, and product leaders passionate about building ethical, usable AI.
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