An open-source agent for getting cited by AI search
The problem
Generative engine optimization was being discussed as an idea and sold as a service, but nobody had written down the operating procedure an agent could follow unattended. A prompt is not a methodology.
What we built
43 nodes across five clusters, each one loadable on demand. An index node routes the agent to the cluster its current task needs, so a citation-monitoring pass never pays for the scraping architecture it is not using.
Monitor, scrape, pay, generate, publish, verify, repeat. Every stage feeds the next, and verification feeds back into monitoring so the strategy adjusts on evidence.
Nine nodes cover x402 micropayments, so an agent can pay for metered or paywalled data mid-run instead of stalling at a signup wall.
A scheduled weekly pass runs the monitoring cluster headless and reports citation gaps with deltas against the previous week. The scheduled version stays report-only: it observes, and a human decides what to publish.
What this demonstrates
Agent-readable methodology: knowledge structured so a model loads only what the current task needs.
Get in touch
Tell us what you are trying to build and what is in the way. We will tell you early if we are not the right fit.