A fact-by-fact comparison of Rankability and Scalenut — sourced and dated — plus the part no generic comparison shows: which one AI assistants actually recommend more, engine by engine.
Measured by Orbator · methodology owner Henrik Telle · window ends Sep 6, 2026
What AI recommends — by engine
Recommendation share = the % of sampled AI answers, over a 4-week rolling window, that recommend each product. Higher is better.
Across the AI engines the Index measures, Rankability and Scalenut are recommended about equally — roughly 0.1% of sampled answers each over the last 4 weeks.
Which AI engines were used to compare Rankability and Scalenut?
Recommendation share is measured on CLAUDE, GEMINI, GROK, CHATGPT, PERPLEXITY using neutral, buyer-shaped prompts (no product names), aggregated over a 4-week rolling window. See the methodology for prompt design and sample sizes.
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Recommendation share and entity resolution follow the Index methodology. Facts are sourced from each vendor's own pages and re-verified periodically. Customer status does not affect measurement. Free to use with attribution to orbator.io.