Contact Meditel Digital
We welcome serious editorial, business, and partnership inquiries related to AI tools, workflow automation, and business technology use-cases.
Primary Contact
Email: azzeddine@haimoud.com
What To Contact Us About
- Corrections or factual updates on published content
- Editorial feedback and quality concerns
- Business collaboration aligned with our AI/business focus
- Requests for clarifications about methodology or comparisons
Editorial Correction Policy
If you identify an error, include the article URL, the specific claim, and supporting references. We prioritize corrections that improve factual accuracy and reader trust.
Response Expectations
We aim to review messages within 2–5 business days. Complex technical requests may require additional verification time.
Important Notes
- We do not provide legal, financial, or compliance consulting.
- We do not sell user data.
- Promotional requests are reviewed only if they are relevant to our editorial scope.
Frequently Asked Questions
Do you publish AI-generated content without human review?
No. AI assistance may be used during drafting, but final publication requires human editorial review, fact checking, and relevance validation for business readers.
How often are pages reviewed?
High-impact pages are reviewed on a recurring basis and after meaningful market changes (pricing, feature shifts, model updates, or policy changes).
How do you handle conflicting vendor claims?
We compare official documentation, independent tests when available, and practical implementation constraints. When uncertainty remains, we explicitly label assumptions and limitations.
Can readers request corrections?
Yes. We accept correction requests with source evidence and update content to improve accuracy and trust.
Methodology Snapshot
Our methodology emphasizes utility for operators: define use-case, compare alternatives, estimate implementation effort, evaluate risk, and map expected value over time. This business-first method reduces tool-chasing and supports better decisions.
Content Governance
We maintain editorial ownership of every page. Automated pipelines are constrained by quality gates. Content that fails usefulness, originality, or credibility checks is revised before publication.
Practical Reader Guidance
Before relying on any recommendation, map the advice to your context: team size, available skills, compliance constraints, and budget limits. Practical implementation quality depends on disciplined scoping, realistic timelines, and clear ownership for each workflow.
For AI/business decisions, we recommend testing with a small pilot, defining measurable KPIs, and documenting expected versus observed outcomes. This approach reduces risk, prevents tool sprawl, and improves decision quality over time.