AI Visibility
measured50/100
Frequently Cited · in FP&A
counts brand mentions in AI answers, not source citations
AEO Readiness
fundamentals33/100
Weak fundamentals
Avg Prompt Score
63
across 327 prompts
AI Share of Voice
63%
across 327 prompts
Critical Issues
3
critical + high
How AI Visibility breaks down
in FP&A
Composite = 50% coverage + 30% engine breadth + 20% position, measured in the brand's strongest category. Position and citation depth join the score once the aggregation pipeline captures them. This is the measured Visibility score — separate from AEO Readiness, which scores fundamentals.
Cited rate · share of voice · engine consensus · sentiment, broken out by buyer-journey stage. Sentiment is the net positive−negative skew across engines that cited the brand at this stage.
Jirav is a B2B FP&A/financial planning SaaS with strong AI-citation inputs from G2 (195 reviews) and active evaluation-stage content (public pricing tiers and multiple first-party “Jirav vs …” style comparison posts). The biggest remaining risk for AI engines is technical/structured-data visibility (SoftwareApplication/FAQPage/AggregateRating not confirmed via search) which can reduce direct inclusion in evaluation and pricing answers.
Based on audit of jirav.com · Oct 2, 2026