Building GetCited From a CLI Script to a Full AI Search Visibility Platform
The Problem
AI search is replacing traditional search for a growing number of users. Over 40% of product research now starts with AI assistants like ChatGPT, Perplexity, and Google Gemini instead of Google. When someone asks an AI "what's the best trading platform" or "who should I buy insurance from," the AI doesn't return 10 blue links. It gives one answer and cites specific websites.
The problem: no tool existed to show businesses which websites AI engines were actually citing. Companies were spending millions on SEO and advertising with zero visibility into whether AI search engines even knew they existed. Traditional SEO tools like Ahrefs and SEMrush track Google rankings, but they don't track AI citations at all.
Anthony Scott, founder of Blueprint Media, saw this blind spot firsthand while working with Fortune 500 clients on SEO and digital marketing. The question kept coming up: "Do AI search engines recommend us?" Nobody had an answer.
The Solution
GetCited was built to answer that question definitively. It sends 25 real customer queries to all 4 major AI search engines, tracks every citation in the responses, and generates a full visibility report showing exactly where a business stands in AI search.
What GetCited Does:
Enter a domain. GetCited generates 25 industry-specific prompts (the exact questions potential customers ask AI), sends them to ChatGPT, Perplexity, Claude, and Gemini simultaneously, collects every website each engine cites, ranks all domains by citation frequency, identifies content gaps, audits the pages that are winning, and delivers a prioritized action plan telling you exactly what to fix.
The tool is completely free. The business model: companies that see their audit results and need help fixing what's broken become consulting clients for Blueprint Media's GEO (Generative Engine Optimization) implementation services.
How It Was Built
Development Timeline
Technical Architecture
The 4-Engine Citation Pipeline
Each AI search engine handles citations differently. GetCited built custom collectors for each:
Full Stack
The Analysis Pipeline
Every audit runs through a 9-step pipeline:
- Configuration — Set up domain-specific database and load prompts
- Perplexity Collection — 25 queries via sonar-pro API
- Claude Collection — 25 queries with web_search tool
- ChatGPT Collection — 25 queries via gpt-4o-search-preview
- Gemini Collection — 25 queries with Google Search grounding
- Source Ranking — All cited domains ranked by frequency across all engines
- Content Auditing — Top-cited pages analyzed for content patterns (word count, headers, schema, structure)
- Gap Analysis — Identify queries where the target domain is missing and who's cited instead
- Report Generation — Full HTML report with scores, leaderboard, gaps, winning patterns, and action plan
The Content Strategy
GetCited doesn't just audit AI visibility — it practices what it preaches. The site was built from the ground up to be cited by AI search engines.
Every article was produced through a 3-agent pipeline:
- Researcher Agent — Gathers data, statistics, and competitive intelligence for the topic
- Writer Agent — Produces the full article with FAQ sections, data-driven insights, and natural language (zero em dashes, conversational tone)
- Grader Agent — Scores for SEO readiness, GEO optimization, readability, and citation-worthiness. Articles below threshold get rewritten.
The content library covers the full spectrum of AI search visibility topics — from foundational guides ("What Is GEO?") to industry-specific playbooks ("AI Visibility for Financial Services") to data-driven studies ("We Audited 50 Websites Across 4 AI Engines"). Every article includes:
- FAQ schema markup — structured data for AI extraction
- Article schema markup — author, publisher, dates for credibility signals
- Key Takeaways box — scannable summary for both humans and AI
- Company hyperlinks — 385 links to companies mentioned (builds authority graph)
- Article interlinks — 218 cross-references between articles (builds topical depth)
- CTA to the free tool — every article drives back to the audit
The AI Readability Stack
GetCited implemented every layer of AI readability available today:
Layer 1: robots.txt — Explicitly allows GPTBot, PerplexityBot, ClaudeBot, and Google-Extended to crawl the full site.
Layer 2: llms.txt — A 3,500-character plain text file at /static/llms.txt describing GetCited's capabilities, products, and content for AI consumption.
Layer 3: Schema.org JSON-LD — Organization, SoftwareApplication, FAQPage, Article, and VideoObject schema on every relevant page.
Layer 4: NLWeb — Microsoft's open-source protocol turning the site into a conversational API. AI agents can POST a natural language query to getcited.tech/nlweb/ask and receive structured, Schema.org-formatted answers sourced from the 52-article content library.
GetCited is one of the first websites in production with a live NLWeb implementation. Any AI agent can query it directly:
The Lead Machine
The business model is elegantly simple: the tool is free, the expertise is not.
The user journey is designed as a natural funnel:
- Discovery — User finds GetCited through blog content, YouTube audit videos, social media, or direct referral
- Engagement — They enter their domain and see 25 custom prompts generated for their industry
- Investment — They've now seen the prompts and want the results. At this point they provide name, email, and phone to launch the audit (lead captured)
- Value delivery — Welcome email sent immediately. Full audit report delivered within 25-30 minutes showing their score, gaps, and action plan
- Conversion — The report reveals problems. The welcome email introduces Anthony and Blueprint Media. The action plan tells them what to fix but not how. That's where the consulting engagement begins.
Every lead is automatically saved to Google Sheets (persists across server deploys), and every submission triggers a welcome email featuring a personal message from Anthony Scott, a breakdown of what the report includes, and a direct CTA to engage Blueprint Media for implementation services.
The Brand Audit Series
To drive awareness, GetCited runs audits on major recognizable brands and publishes the findings as video content and social media posts. The first audit — Progressive Insurance — became the blueprint for the series.
Progressive Insurance Audit Findings:
Score: 79.9/100. Ranked #5 out of 186 domains. Beaten by Insurify, MoneyGeek, TheZebra, and NerdWallet — none of which are actual insurance companies. 32% of AI queries returned zero Progressive citations. On Perplexity alone: 2 citations vs Insurify's 18.
The most shocking finding: when someone asks AI "Progressive vs State Farm," Progressive isn't cited in their own comparison. Third-party blogs are answering that question for them.
Five additional brand audits were prepared for the series: Tesla, Nike, Coinbase, Shopify, and HubSpot — each selected for maximum audience reach and viral potential. Each audit includes a full YouTube video package with script, thumbnail concepts, YouTube description, hashtags, and short-form clip suggestions.
Marketing Infrastructure
A complete marketing playbook was built covering 8 free traffic channels:
- YouTube — Weekly brand audit video series with full production packages
- LinkedIn — 5 posts/week across 4 content formats (audit findings, industry insights, behind-the-build, video clips)
- Reddit — Targeted presence in r/SEO, r/marketing, r/artificial, r/SaaS, r/Entrepreneur, r/digital_marketing
- Dev.to — Technical articles on the 4-engine citation pipeline and NLWeb implementation
- Indie Hackers — Building-in-public product launch and weekly updates
- Product Hunt — Scheduled launch with full asset preparation
- Direct Outreach — Email audited brands' marketing teams with their reports
- Google Search Console — Organic traffic monitoring for 52 indexed articles
The entire playbook was packaged as an HTML delegation document that can be handed to an assistant for execution — complete with templates, checklists, posting schedules, and platform-specific rules.
What Was Built
From a single Python CLI script to a production SaaS with 4-engine citation tracking, 52 articles, NLWeb integration, automated lead capture, email delivery, and a complete marketing engine. Every piece was built to work together: the content drives traffic, the free tool converts visitors to leads, the audit report demonstrates the problem, and Blueprint Media solves it.
"I built this tool because I saw a massive blind spot in digital marketing. Companies spending millions on advertising had no idea whether AI search engines even knew they existed. The brands that show up in AI results aren't always the biggest. They're the ones with the right content structure, the right technical setup, and the right strategy."