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

Comments URL: https://news.ycombinator.com/item?id=44567744

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