Guide
llms.txt for SaaS
An llms.txt file gives AI retrieval systems a concise, public summary of your SaaS brand, product, audience, important pages, and evidence limits.
Treat llms.txt as a machine-readable table of contents for public facts, not as a private data feed or a way to force AI recommendations.
Target query
llms.txt for SaaS
What to include
A SaaS llms.txt should describe the brand, product category, ideal customer, core use cases, pricing or plan page, documentation, comparison assets, and contact path.
- Link only to public pages that should be cited.
- Summarize what the product does in plain language.
- State evidence limitations when AI visibility claims are diagnostic.
- Keep private reports, APIs, tokens, and customer data out of the file.
Why it matters for AI retrieval
AI systems still need accessible source material. A clean llms.txt can help retrieval systems and auditors find the right public pages faster, especially when the site has many app, docs, or marketing paths.
Common mistakes
The most common mistakes are treating llms.txt as a ranking hack, linking private URLs, stuffing keywords, or claiming official AI visibility without observed evidence.
How to validate
After publishing, confirm `/llms.txt` returns 200, uses plain text, links only public pages, and appears in the sitemap or footer resources when appropriate.
FAQ
Does llms.txt guarantee AI tools will cite my SaaS?
No. It can make public information easier to discover and audit, but it does not guarantee citation, ranking, or recommendation in any AI product.
Should llms.txt include private report links?
No. Keep protected reports, APIs, tokens, payment links, and customer data out of llms.txt. Link only to public marketing, docs, pricing, guide, and resource pages.
Run the same check on your public site
Start with a free VisAI Snapshot Preview, then use the Agent-Ready Standard and pricing page to decide whether a protected Starter Snapshot is worth unlocking.