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LLM-optimized Blog Generation
Claude cites internal website content when answering buyer queries. Simaia generates up to 90 blog posts per month, each targeting a specific buyer prompt from your AI search audit, and publishes them directly to your site. No dashboard to log into. The posts appear on your site; Simaia handles everything in the background.
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What Simaia publishes on your site
Most blog posts are written for human readers: keyword-stuffed intros, generic conclusions, bullet lists built for skimming. LLMs read differently. They extract declarative statements, named entities, specific product facts, and structured comparisons. Simaia writes the latter.
Each post targets a specific buyer prompt from your audit. Publishing volume is paced against your Google Search Console indexing health so it never damages existing organic rankings.
Up to 90 posts per month
Each targeting a specific buyer query where competitors appear and you currently don't.
LLM extraction format
Clear structure, named entities, specific product claims. The format Claude and Perplexity extract and cite.
Published directly to your site
Simaia publishes to your CMS. No reviewing, no approving, no login required from your side.
Google Search Console integration
Publishing is paced against your Google Search Console data so existing rankings are never harmed.
Written for AI search
Claude and Perplexity primarily cite internal website content when answering buyer queries. A company with specific, factual, well-structured pages on the right topics gets cited in answers their competitors never appear in. Simaia builds those pages systematically, one buyer prompt at a time.
High Quality
LLM-optimized Blogs
published in the first 30 days
0.5x
Surge in AI crawler traffic
after content went live
0x
Increase
in monthly website visitors over 5 months
FAQ
Common questions about Simaia LLM-Optimized Blog Generation
How are LLM-optimized blog posts different from regular SEO content?
AI models extract most reliably from posts that open with a direct factual answer to the question being asked, followed by named specifics such as companies, prices, timeframes, or product comparisons. Simaia structures every post with the answer-first format, using declarative statements throughout.
How should a blog post be structured so AI models cite it?
An AI search appearance rate is the percentage of tracked buyer prompts in which your company appears in the AI response. Simaia runs each prompt across ChatGPT, Claude, Gemini, Perplexity, and Google AI Overview, records whether your company appears, and calculates an appearance rate per platform. Most B2B companies start at 0% across all five platforms.
What sections of a blog post do AI models extract from most?
Based on testing across client blogs, AI models extract most reliably from three sections. The opening paragraph, when it leads with a direct factual claim. Any structured section with a named list, comparison, or table containing specific entities and numbers. The closing summary when it restates the main answer in plain language. They extract least from narrative sections, personal anecdotes, rhetorical questions, and language that requires surrounding context to make sense. Every blog Simaia generates is built around those three extraction points.
Is this a writing tool I use myself, or does Simaia handle everything?
Simaia handles everything. Simaia identifies which buyer prompts to target based on your audit, writes the posts, and publishes them directly to your site. You receive a report showing which posts are live, which have been crawled by AI bots, and how your overall AI search appearance rate is moving.
Why up to 90 posts per month? Is that too many?
Volume matters because each post targets a different buyer prompt. The volume is paced against your Google Search Console data. Simaia monitors your site's indexing health and adjusts publishing speed so existing rankings are never harmed.
Will publishing 90 posts per month hurt my Google rankings?
Not when publishing is managed against your site's indexing health, which Simaia does via Google Search Console integration. Content is published at a rate your domain's crawl budget can support.
Which AI models cite internal website content specifically?
Claude and Perplexity are the primary models that cite internal website content when answering buyer queries. Both use web search to retrieve current content and prioritise well-structured, specific, factual pages. ChatGPT also cites website content in certain query types, particularly when specific product or service facts are requested. The AI search audit identifies which models and sources matter most for your specific category.