The logic underneath f1frp
f1frp is not the kind of thing you solve by stacking more data. What actually determines its value is how the AI Agent × structured data × engineering delivery three layers connect, how the nodes link, and how content compounds. This page set lays out the architecture, advantages, current capabilities, and the next-year roadmap.
Next.js 16 · PostgreSQL + pgvector · Gemini + Claude + OpenRouter · daily cron ingestion. The whole site is a content flywheel that never stops.
Citation-first AI, multi-source auto-ingestion, bilingual by design, content that grows daily. Not a feature upgrade — a different operating model.
One-sentence AI material selection, paper/patent verification, RFQ routed to suppliers, process wiki + calculators, standards lookup, supplier claiming. Six core scenarios live.
Agent tool-calling, private workspace, AI deliverables, CBAM compliance, cross-border RFQ, data API, expert network — all on the roadmap.
AI on top, data in the middle, engineering at the base
Select · Formulate · Standards · Paper commentary · Supplier match — every statement cites a source, never hallucinates
Six interconnected libraries: materials, formulas, standards, papers, patents, suppliers — every parameter traceable
RFQ / sample request / downloads / calculators / PDF reports — built for engineers who need to ship