No score theater. These are measured before/after results from FirePencil's autonomous AEO agent, drawn from real audit and search data.
Academic Journal · 48 hours
IJARST: from an unindexable 0/100 to a 94–98/100 AEO foundation
An academic journal whose every page served the same title, with zero Google Scholar citation tags, so AI and Scholar literally couldn't tell its papers apart. Here's the full before/after of what the agent found, fixed, and measured.
AEO health 0 → 98/100
Critical blockers 6 → 0
Scholar unindexable → indexable
TTFB ~2× faster
Read the case study →
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Case studies report individual clients' measured before/after data and are not a guarantee of any specific outcome. Scores reflect FirePencil's AEO-readiness model; search metrics are from Google Search Console. Third-party names (Google, Google Scholar, ChatGPT, Gemini, Perplexity, Claude) are trademarks of their respective owners; use is descriptive.
Frequently asked questions
What results does FirePencil's AEO agent produce?
Measured before-and-after improvements. For example, the academic journal IJARST went from an unindexable 0/100 to a 94-98/100 AEO foundation in about 48 hours, with Google Scholar indexing unblocked and a real organic search footprint.
Are these case study results typical?
Every site is different. The case studies report individual clients' measured data from audits and Google Search Console, not guarantees. Speed depends on how fixable the technical foundation is.
How does FirePencil measure case-study results?
From first-party data: the site's own audit scores plus Google Search Console impressions and clicks, alongside multi-engine AI citation sweeps, so the before/after is defensible rather than estimated.
