Sitefire Launches Automation Platform to Enhance Brand Visibility in AI Search

The company focuses on the mechanism where AI search engines expand a user's prompt into 3 to 10 fan-out queries and rank pages using algorithms similar to Reciprocal Rank Fusion (RRF). Ultimately, an LLM reads the pages and determines which snippets to cite.

Sitefire generates synthetic prompts based on SEO keywords and monthly search volumes, sending them daily to ChatGPT, Gemini, Google AI Mode, and other tools to retrieve responses. From these, it extracts fan-out queries, source pages, citations, and brand mentions.

Based on the extracted data, agents analyze which web pages are most frequently sourced and cited, and why. Taking existing similar pages into account, a content agent drafts improvement suggestions or creates new pages based on the diagnosis. The generated content is then pushed directly to the client's CMS.

Traffic growth is monitored through integration with client network logs and Google Analytics, tracking changes in the number of requests from AI bots and referrals from humans.

It has been reported that after optimizing a client's blog, AI bot requests increased from approximately 200 to approximately 570 per day over a 10-day period.

To counter "slop" (low-quality mass generation) caused by AI-generated content, the platform aims to produce content focused on concrete and unique information, such as actual product features, pricing, and honest comparisons. Before publication, clients review all pages to ensure alignment with their brand.

Two service models are available: a self-service model operated by the client and an agency model where Sitefire executes the automation steps. The company stated that it aims for full automation in the future, where clients only need to approve changes via Slack, Claude, or their CMS.