Proof of Usefulness Report

RankRush

Analysis completed on 5/20/2026

+64

Proof of Usefulness Score

You're In Business

RankRush addresses a highly relevant and rapidly emerging market need (Generative Engine Optimization for LLM discovery) with a well-architected modern tech stack. The submission is highly transparent and detailed. However, despite processing high volume automated visibility scans, actual human user traction remains minimal (16 MAU, 2 paying customers). The project shows excellent potential and market timing but scores on the lower end of the PoU scale due to its current nascent audience size and revenue base.

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Score Breakdown

Real World Utility+24.00

Audience Reach Impact+2.00

Technical Innovation+13.50

Evidence Of Traction+4.13

Market Timing Relevance+10.80

Functional Completeness+6.18

Subtotal+60.61

Usefulness Multiplierx1.05

Final Score+64

Project Details

Project URL

rankrush.ai/

Description

RankRush helps small SaaS and service businesses get cited by AI search engines (ChatGPT, Perplexity, Gemini) — scoring each brand's AI discoverability, auditing the technical SEO gaps blocking LLM ingestion, and running Reddit community campaigns that build the citation signals AI engines reward. Built on Supabase + Gemini, with three modules: Core (visibility scoring + audit), Buzz (Reddit engagement), and a Python CLI (rr-cli) for power users.

Audience Reach

RankRush has been live for ~4 months (first signup 2026-01-24). Current monthly footprint: 16 monthly active users across 45 total signups — with 17 new signups in the last 30 days (~38% of all signups, indicating active growth). The product runs ~265 AI visibility scans per day (~7,934 last month, 8,918 lifetime) plus 174 full website audits in the last 30 days (242 lifetime). Across these scans, RankRush has analyzed 3,555 unique brands' AI discoverability — meaning the actual public-utility surface (LLM-citation insight) is an order of magnitude larger than the user count.

Target Users

Small SaaS founders, service-business owners, and indie marketing teams who notice their product isn't being mentioned by ChatGPT / Perplexity / Gemini and want to fix it without paying an SEO agency $5K/month. Also: marketing agencies (we have an active agency-tier customer running multi-client visibility tracking). Notable customer signals: 2 currently-paying accounts across the starter and agency tiers, validating both the indie-hacker and the agency use cases from a small base.

Technologies

Other, Frontend: React 18, TypeScript 5, Vite 5, Tailwind CSS, shadcn/ui, TanStack Query v5. Backend: Supabase (Postgres + Row-Level Security + Deno Edge Functions + pg_cron + pgmq). AI: Google Gemini 2.5-flash (strategy + classification) and Gemini 2.5-flash-lite (research). External: Firecrawl (Reddit + web scraping), Reddit API (OAuth posting), Stripe (billing), Resend (transactional email). Marketing site: Astro 6 on Cloudflare Pages + Workers. CLI: Python 3 (rr-cli), packaged for PyPI. CI/CD: GitHub Actions, Cloudflare Pages PR previews via Wrangler.

Traction Evidence

https://rankrush.ai — live marketing site (Astro, Cloudflare Pages) https://app.rankrush.ai — production application 8,918 AI visibility scans run since launch (2026-01-24) — 7,934 in last 30 days 3,555 unique brands analyzed across user-initiated scans 242 full website audits completed 45 signups · 16 MAU · 2 paying accounts (1 agency-tier, 1 starter)

Algorithm Insights

Market Position

Growing utility with room for optimization

User Engagement

Documented reach suggests active user community

Technical Stack

Modern tech stack aligned with sponsor technologies

Recommendations to Increase Usefulness Score

Document User Growth

Provide specific metrics on user acquisition and retention rates

Showcase Revenue Model

Detail sustainable monetization strategy and current revenue streams

Expand Evidence Base

Include testimonials, case studies, and third-party validation

Technical Roadmap

Share development milestones and feature completion timeline