Who built AEOForged?

How was AEOForged created?

AEOForged was created by applying expertise from two converging fields — blockchain algorithm engineering and AI agent development — to a problem most businesses don't yet know they have.

The first domain was blockchain. Ryan Kings spent several years building automated arbitrage systems — algorithms that monitored decentralised exchanges in real time, identified pricing inefficiencies, and executed trades autonomously. That work required building reliable pipelines for live data, making decisions under uncertainty at machine speed, and running systems 24/7 without intervention.

The second domain was AI. He moved into building AI agents and intelligent automation tools — systems that could evaluate information, reason about it, and act on it without human direction. The common thread across both fields: teaching machines to find, assess, and respond to information faster and more reliably than manual processes allow.

The insight behind AEOForged was that AI answer engines — ChatGPT, Perplexity, Google AI Overviews, Claude — face the same challenge those trading algorithms did. They need to rapidly evaluate content, extract the best answer, and decide what to cite. The difference is that most businesses have no visibility into that process and no way to influence it.

AEOForged was built to close that gap. The algorithmic thinking from blockchain and the autonomous intelligence from AI agent work were channelled into a purpose-built content intelligence platform — 25 tools covering research, scoring, auditing, content creation, and citation monitoring. The result is an 8-dimension system that quantifies exactly how extractable and citable your content is, and tells you precisely what to fix.

How does the AEO scoring system work?

AEOForged scores content across 8 dimensions that map to how AI answer engines evaluate and select content for citation. Each dimension is scored independently, and the total gives a 0–100 measure of how extractable and citable your content is by engines like ChatGPT, Perplexity, and Google AI Overviews.

The scoring methodology draws on Google's structured data guidelines, E-E-A-T quality frameworks, and analysis of how AI models select and cite sources in their responses. Every deliverable AEOForged produces includes before-and-after scores so improvements are quantifiable, not subjective.

What does AEOForged do?

AEOForged is an answer engine optimization platform with 25 tools covering the full content lifecycle. The platform provides research, scoring, auditing, content creation, and citation monitoring — all designed to get your content cited by AI answer engines like ChatGPT, Perplexity, Google AI Overviews, and Claude.

How do AEOForged's algorithms work?

AEOForged uses proprietary algorithmic analysis to evaluate content against the same criteria AI answer engines use when selecting sources to cite. The system operates across 8 scoring dimensions simultaneously, producing a composite 0–100 score that quantifies citability with precision.

The research layer pulls live data from multiple sources, synthesises entities, claims, and competitive positioning, then feeds that intelligence into the scoring and content pipelines. Each dimension uses specialised heuristics — measuring structural patterns, declarative sentence density, entity coverage ratios, schema type completeness, and trust signal distribution — to produce scores that correlate with real-world AI citation behaviour.

The audit pipeline goes further: it crawls entire sites, evaluates every discoverable page, benchmarks against competitors, and generates prioritised improvement plans ranked by projected score impact. The scoring feedback loop means clients can measure before-and-after improvements with the same algorithmic precision used by the audit itself.

The underlying methodology draws on Google's structured data documentation, E-E-A-T quality guidelines, and extensive analysis of how large language models retrieve and rank source material.