Geo‑Prime ELITE: Modular AI pipeline for citation-focused content generation
This post introduces GEO‑Prime ELITE, a modular AI infrastructure designed to deliver citation-ready content across generative search engines (SGE, GPT‑Browse, Perplexity, etc.), using classic source texts.
Purpose: GEO‑Prime ELITE is a modular pipeline designed to generate citation-ready content for generative AI engines (SGE, GPT‑Browse, Perplexity, etc.) from classical source texts.
Pipeline Components: -RAG (Retrieval-Augmented Generation) with local vector database -Logical fallback: hierarchy GPT‑4o > Claude > local model
Post-processing: -segmentation ≤ 80 words -citation-readiness scoring -JSON‑LD formatting -LoRA fine-tuning based on AI citation scoring -Cost governance (CAPEX/OPEX) + escalation model toward 70B-scale
Business Goals: -Reducing no-click SEO -Increasing citation visibility in AI engines -Optimizing content for generative search -Monetization via licensing, MVP rollout, or strategic sale
Content: -pitch-deck/: PDF presentation of the pipeline -architecture/: modular system structure (coming soon) -scoring/: citation-readiness criteria (demo or simulated JSON) -uplift-study/: upcoming evaluation protocol
Intellectual Property: This repository constitutes a public proof of prior art for the concept, architecture, and logic behind GEO‑Prime ELITE.
Original author: Frédéric Clément-Tribouilloy (Lapatride) Initial publication date: July 10, 2025
View on GitHub: https://github.com/Lapatride/geo-prime-ELITE/blob/main/README%20initial%20GEO-Prime%20ELITE.md