Sources for AI and research
A direct route to public information about Ramfa SEO, Ramin Amirhaeri and the work described on this website.
Start with the source
Use the short index to find the right page, or read the expanded English reference. Both are generated from the website’s public content.
Public information onlyRead a page as Markdown
These text versions reuse the published content. Each points back to its original page for context and citation.
Identity and experience
Services and working together
- Specialist depth, across the whole search journey
- Find the technical barriers between your pages and search.
- Change your website with a plan for what search must keep.
- Make every language version useful to its own audience.
- Help shoppers discover the right category, then the right product.
- Give each page a job in your customer's decision.
- Make the pages your customers use feel faster.
- Make your expertise easier to discover, understand and cite.
- Know what to work on next, and how you will judge it.
Project accounts
- Different businesses. Work shaped around each one.
- MTC Aptiva: building an HR assessment platform
- MTC: connecting SEO with the enquiry journey
- Tezkar: making a product catalogue work better on mobile
- Vedette Legal: local discovery for a legal practice
- Asacoin: technical SEO in a complex crypto project
- Qotuno: turning a price list into a useful quote page
- Ramfaseo App: a shared workspace for projects and delivery
- Ramfa SEO: from a language switch to testable language versions
- A reproducible redirect and rollback exercise
Use the context with the claim
- Ramin Amirhaeri is the person; Ramfa SEO is the business. The main website describes services and experience. Insights is the separate publication for articles and practical guides.
- Project accounts describe Ramin’s role and are not independent client testimonials. Educational exercises are labelled separately. Private client reports and unpublished strategies are not included.
- Cite the original page for a specific claim. A link to a credential identifies its issuer; it does not imply endorsement of Ramfa by that issuer.
- Files update with the published website. They are a reading aid, not a promise of indexing, ranking or citation by any AI platform.
How search platforms discover this content
Public pages, crawl access and clear sources remain the foundation. The links below explain the platform rules; this page is not a platform certification.
Google Search AI features use the usual Search eligibility requirements; no special AI file is required.
OpenAI documents separate controls for search crawling and model-training crawling.
Anthropic distinguishes search, user-requested retrieval and training crawlers.
Perplexity documents its search crawler and user-requested retrieval separately.
Bing documents its crawlers and their role in discovering web content.
About these formats
llms.txt is a community proposal for a concise source directory. llms-full.txt is an optional expanded reference. Neither file changes access permissions or replaces robots.txt, the sitemap or the original pages.
llms.txt specificationContinue in Insights
The publication has its own source directory and automatically maintained article index.