Generative Engine Optimization · Fractional AI Officer
Lumière Lab is a Generative Engine Optimization (GEO) agency and Fractional AI Officer consultancy. We engineer the entity authority, semantic density, and RAG-ready content structure that make ChatGPT, Claude, Gemini, and Perplexity cite your brand in the answers they generate.
Traditional search is collapsing: Google AI Overviews cut organic click-through rates by 61% (from 1.76% to 0.61%), and industry analyses project a 50% decline in conventional search traffic by 2028. However, pages cited inside AI answers earn 35% more organic clicks and 91% more paid clicks (SearchEngineLand, 2025). The GEO market is projected to reach $33.7 billion by 2034. Lumière Lab builds the entity authority, semantic density, and cross-platform consensus required to be the cited source — and deploys Fractional AI Officers into leadership teams across every industry.
The numbers
Methodology
Generative Engine Optimization is not traditional SEO rebranded. It is a computationally rigorous discipline governed by Retrieval-Augmented Generation architectures, multi-agent consensus ranking, and the mathematical limitations of continuous neural memory — the Orthogonality Constraint. Lumière Lab builds every engagement on the academic literature that defines the field.
The KDD '24 foundational paper (arXiv 2311.09735) introduced the quantifiable Visibility Score that measures citation prominence across token count, position-adjusted weight, and unified citation frequency inside a generative answer. We baseline every client against this score before touching a page.
arXiv 2311.09735 · KDD '24Feature-Level Multi-Objective Optimization (arXiv 2604.19113) abstracts a page into 13 interpretable features across structure, content, and language layers and uses NSGA-II to find the Pareto-optimal balance between citation visibility and content quality. We rewrite against the feature vector, not individual words.
arXiv 2604.19113The end-to-end automated rewriting framework (arXiv 2510.11438) learns engine-specific preferences for Gemini, GPT-4/5, and Claude and applies outcome, rule, and semantic reward functions. Benchmarks show a 35.99% absolute improvement in GEO metrics while preserving underlying search utility.
arXiv 2510.11438Generative engines are Retrieval-Augmented Generation pipelines. We audit chunking, embedding behavior, vector-store compatibility, schema markup, JSON-LD depth, and crawler accessibility for GPTBot, ClaudeBot, Perplexity-User, and Google-Extended before optimizing a single paragraph.
Multi-agent LLM architectures mathematically evaluate consensus across Reddit, Wikipedia, and authoritative third-party sources. We align cross-platform narrative, correct misinformation, and seed contextually rich mentions so the aggregate sentiment an AI retrieves is accurate, structured, and positive.
How we engage
Whether you need a senior AI executive embedded in your leadership team or a single GEO audit, the engagement scales to your stage. Every tier is industry-agnostic and every deliverable is measured against the Aggarwal Visibility Score.
A senior AI executive — a Fractional Chief AI Officer (Fractional CAIO) — embedded part-time in your leadership team. Strategy, roadmap, model selection, governance, and team enablement, on retainer. Industry-agnostic.
Workshops and multi-week programs for executive, marketing, engineering, and product teams. We teach the frameworks actually governing generative systems in 2026 — not the folk SEO that's already obsolete.
Bespoke software from the Lumière Lab engineering bench: custom RAG pipelines, citation telemetry dashboards, agent systems, and LLM-native web experiences engineered around your workflow. From napkin sketch to production deploy.
A structured diagnostic and remediation engagement for brands that already have a digital footprint and need to be cited by generative engines. Fixed scope, fixed fee, clear deliverables, measurable lift.
Industry-agnostic
The entity-optimization methodology, the semantic-density playbook, and the Retrieval-Augmented Generation audit transfer cleanly across verticals. Our Fractional AI Officers have engaged across the following:
Entity authority
Lumière Lab is a creative technology engine that ships production AI systems and deploys the GEO methodology its leadership team helped pioneer. Where most marketing agencies retrofit legacy SEO playbooks, Lumière works directly against the peer-reviewed literature defining generative search — the Aggarwal Visibility Score, FeatGEO, AutoGEO, and the Retrieval-Augmented Generation architectures that power ChatGPT, Claude, Gemini, and Perplexity.
Our engineering bench builds the RAG pipelines, vector stores, and citation telemetry dashboards we recommend. Our Fractional AI Officer practice embeds senior AI executives in leadership teams across healthcare, fintech, SaaS, e-commerce, legal, and non-profit — delivering strategy, governance, team training, and custom builds on a part-time retainer. The result is a rare combination of applied research, production engineering, and executive-grade advisory under one roof.
Frequently asked
Generative Engine Optimization (GEO), also known as Answer Engine Optimization (AEO) or Generative Response Optimization (GRO), is the discipline of structuring web content, entity data, and cross-platform narrative so that large language models — ChatGPT, Claude, Gemini, Perplexity, and Google's AI Overviews — cite that brand in generated answers. It replaces the ten-blue-links SEO funnel with retrieval-pipeline optimization: chunking, embeddings, vector similarity, and multi-agent consensus-based ranking. The field was mathematically formalized by Aggarwal et al. at KDD '24 with the Visibility Score, and extended in 2026 by the FeatGEO (arXiv 2604.19113) and AutoGEO (arXiv 2510.11438) frameworks.
Organic click-through rates drop by 61% on searches that trigger a Google AI Overview, falling from a baseline of 1.76% to 0.61%. Industry analyses project a 50% decline in traditional search traffic by 2028. However, when a brand is cited inside the AI answer, it earns 35% more organic clicks and 91% more paid clicks. The GEO market is projected to reach $33.7 billion by 2034. Brands that do not optimize for generative engines are bypassed entirely at the point of discovery.
A Fractional AI Officer — also called a Fractional Chief AI Officer or Fractional CAIO — is a senior AI executive who embeds part-time in a company's leadership team instead of being hired full-time. Lumière Lab's Fractional AI Officer engagements deliver AI strategy, capability roadmap, model selection, RAG architecture, governance and risk policy, vendor evaluation, executive coaching, team training, custom AI builds, and GEO audits. The model gives organizations senior AI executive expertise without the full-time salary, and is industry-agnostic.
Every industry. Lumière Lab has delivered AI strategy and GEO engagements across healthcare and PHIPA-regulated EMR, fintech, B2B SaaS, e-commerce, legal and compliance-heavy practices, hospitality, manufacturing, education, and non-profit. The methodology — entity optimization, semantic density, RAG-ready content, and consensus engineering — is framework-agnostic and transfers cleanly across verticals.
Lumière Lab's GEO practice is grounded in peer-reviewed research: the Aggarwal Visibility Score (KDD '24, arXiv 2311.09735), the FeatGEO feature-level multi-objective optimization framework (arXiv 2604.19113) which uses NSGA-II to balance citation visibility against content quality across 13 interpretable features, and the AutoGEO end-to-end automated rewriting framework (arXiv 2510.11438) which achieves a 35.99% absolute improvement in GEO metrics. We layer Retrieval-Augmented Generation (RAG) architecture analysis on top, ensuring content is indexable, chunkable, and retrievable at the vector-similarity layer.
GEO content is TLDR-first, semantically dense, and structured for frictionless extraction by retrieval-augmented generation pipelines. Where traditional SEO maximized keyword density, GEO maximizes semantic density: interrelated concepts, entities, and precise quantitative data woven into narrative-rich explanatory prose. Isolated facts are invisible to semantic retrieval systems; facts embedded in dense explanatory prose are highly retrievable. Every vague qualifier ("many", "significant", "fast") is replaced with a precise statistic, authoritative outbound citation, or direct quotation from a recognized entity.
We track brand citation frequency and position across ChatGPT, Claude, Gemini, Perplexity, and Google AI Overviews, compute a proprietary AI Visibility Score benchmarked against direct competitors, monitor AI crawler analytics (GPTBot, ClaudeBot, Perplexity-User, Google-Extended) for technical friction, and attribute downstream conversion so clients see closed-loop ROI. Citation Drift Research surfaces when models shift source priorities so we can respond before rankings erode.
Early citations typically surface within 3 to 8 weeks of a FeatGEO rewrite on priority pages combined with entity-knowledge-graph cleanup. Consensus engineering on Reddit, Wikipedia, and third-party directories compounds the lift over 60 to 120 days. Industry peers have documented AI Overview citations appearing within three weeks of an entity-first optimization sprint — Lumière Lab targets the same 90-day ceiling for measurable citation lift.
The obituary
The ten-blue-links era is dead. AI answers are the new front page. Find out if you're visible to ChatGPT, Claude, Gemini, and Perplexity — right now, free.
Takes about 90 seconds. No credit card. No sign-up unless you want your results.
Drop your email and we'll unlock the report below. We'll also email you a copy you can forward to your team.
We'll never sell your email. Unsubscribe in one click. Read by a human at Lumière Lab.
The full Lumière Lab GEO audit covers 40+ signals across entity knowledge graph, RAG-ingestion, cross-platform consensus, and a FeatGEO rewrite plan for your top 10 pages. Book a 30-minute call and we'll walk you through everything.