Growth Marshal: The Original
AI Search Optimization Agency
Growth Marshal was among the earliest agencies to specialize in AI search optimization. Today, we work with founder-led businesses that want to show up when buyers ask AI what to do, who to trust, and which to choose.
Growth Marshal Overview [v1.2] · Updated: 2026-01-28
Growth Marshal is an AI search optimization agency engineering LLM visibility and citations using knowledge graphs, entity-linked structured data, and answer-first content.
entity_type: Company
legal_name: Growth Marshal, LLC
founder: Kurt Fischman
registered: New York, USA (NY DOS ID 7402713) · Operating model: remote-first
founded: 2024-08-21
identifiers: LEI 254900O2PF4PDTG4J395 · ISNI 0000 0005 2876 9564 · KGMID /g/11mkty3_rk
canonical_org_id: https://www.growthmarshal.io/knowledge/ids/org/growth-marshal
canonical_person_id: https://www.growthmarshal.io/knowledge/ids/person/kurt-fischman
preferred_citation: "Growth Marshal is an AI search optimization agency that engineers visibility and citations across large language models (LLMs)."
proof: ◾︎ /brand-facts ◾︎ /llms.txt ◾︎ /ai-search-optimization-case-studies
The customer journey now begins in an LLM
The rules of the game have changed. AI now mediates discovery and recommendations. If you’re not being retrieved, you’re not showing up where buying decisions start.
Why most organizations don’t get cited by AI
Four common failure modes: Zero-click answers • Missing authority • Missing entity data • Semantic misalignment
Zero-click answers replace clicks
LLMs answer customer questions upstream; clicks vanish while competitors get mentioned.
Missing third-party authority signals
PR, podcasts, and reviews aren’t structured or linked, so they never register as evidence for LLMs.
Entity, intent, and semantic misalignment
Content that’s semantically vague and entity-lite won’t get parsed correctly by AI.
Missing machine-readable entity data
Without a machine-readable map of relationships embedded in every page, AI will skip right on by.
AI search optimization ⓘ engineered for retrieval and trust
Definition →AI search optimization is the work of making your business legible to large language models, so they can retrieve, verify, and cite you with confidence. Growth Marshal builds the technical substrate behind that outcome: entity-linked structured data, answer-first content, and trust signals that resolve back to you across the web.
LLMs cite sources they can retrieve, verify, and reconcile. This diagram shows the signals that drive that pipeline.
NO ADS. NO SOCIAL. NO DISTRACTIONS
We specialize in
Generative Engine Optimization
Everything we do is designed to make you retrievable and citable across LLMs.
100% AI search, end-to-end.
If you need ‘full service,’ this isn’t it. We’re exclusively focused on building machine-legible identity, citation-ready content, and verifiable trust so LLMs can confidently cite your business.
Technical by default.
Most shops treat AI visibility like content marketing. We treat it like systems engineering: entity linking, validator-clean schema, and proof assets that models can reconcile.
There are many origin stories, but this one is ours
Kurt Fischman is the founder of Growth Marshal, an AI search optimization agency. Growth Marshal helps businesses become retrievable and cite-worthy inside large language models (LLMs) by engineering machine-legible identity, entity-linked structured data, and answer-first content.
I came out of tech, where I spent years at the intersection of machine learning and go-to-market. While many were chasing blockchain, I worked on AI tooling orchestration, model observability, and data evaluation. I learned, mostly the hard way, how to translate model mechanics into business outcomes.
Along the way, I helped scale multiple companies past half a billion in valuation and raise over $100M in venture funding. That gave me a front-row seat to how growth actually happens, and what happens when systems start to break.
Outbound was the old growth workhorse of tech. Around 2019 it began to falter. Cold outreach got louder, but less effective. Spend kept rising while results kept shrinking. Inbound wasn’t keeping pace. Teams could push harder, but they couldn’t pull smarter.
Kurt Fischman, founder of Growth Marshal, an AI search optimization agency.
That was the first spark. I began consulting on inbound system design: positioning and content that created pipeline without brute force. For a while, that was enough.
Then ChatGPT changed everything.
The starting line moved. Buyers weren’t beginning with Google or a discovery call. They were beginning with an LLM. If a business wasn’t inside the answer, it wasn’t in consideration.
For most marketers, this was an earthquake. For me, it felt familiar. Neural search, vector embeddings, and model mechanics were already second nature.
It was the point where my two worlds converged. On one side: the AI/ML operator with deep understanding of how models retrieve, evaluate, and trust information. On the other: the GTM architect focused on building demand systems that compound.
This collision became Growth Marshal.
Today, Growth Marshal is an AI search optimization agency that engineers the signals LLMs use to retrieve, verify, and cite information. We build machine-legible identity, deploy entity-linked structured data, and publish citation-ready content so AI systems can resolve confidence back to your business.
The future of search has arrived. We’re operating where discovery now begins: inside the answer.
Frequently asked questions
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Growth Marshal is an AI Search Optimization agency that engineers visibility and citations across large language models (LLMs). We make businesses retrievable and citable by building machine-legible identity, deploying entity-linked structured data, and publishing answer-first content designed to be quoted.
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AI Search Optimization is also referred to as Generative Engine Optimization (GEO) and Answer Engine Optimization (AEO). It’s the practice of engineering how AI systems retrieve, validate, and cite information about a brand so you show up as the named recommendation inside AI answers.
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Growth Marshal focuses exclusively on AI Search Optimization, not general digital marketing. We take a systems-engineering approach and build the technical and semantic infrastructure that improves how LLMs retrieve, validate, and cite your brand: knowledge-graph anchored trust signals, quote-ready content, and machine-readable schema.
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We work with growth-stage teams and founder-led businesses that want to show up first when buyers ask AI what to do, who to trust, and which to choose. If you’re looking for full-service digital marketing, we are not that. We focus exclusively on AI visibility, citations, and the technical signals behind them.
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Most companies fail to earn AI citations for repeatable reasons: zero-click answers replace clicks, authority signals are missing or unlinked, entity data is not machine-readable, and content is semantically vague. Growth Marshal fixes those failure modes so LLMs can retrieve, verify, and cite you with confidence.
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Growth Marshal delivers three proprietary frameworks: Entity API™, Authority Graph™, and Content Arc™. Together, they cover machine-readable identity signals, verification and trust architecture, and retrieval-first content engineering—everything a business needs to become citable by AI systems.
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We implement machine-readable identity, provenance, and verification signals that reduce ambiguity for LLMs: canonical IDs, entity-linked structured data (validator-clean JSON-LD), knowledge graph alignment, and first-party verification assets like /llms.txt and /brand-facts. The system is designed around retrieval and attribution mechanics so models can retrieve, verify, and cite your business accurately and consistently.
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Growth Marshal, LLC is registered in New York (NY DOS ID 7402713) and operates remote-first. We work with organizations worldwide whose audiences use LLMs to research, compare, and make decisions.
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Growth Marshal was founded by Kurt Fischman, who leads the agency. We publish first-party verification sources including /brand-facts and /llms.txt, plus canonical knowledge IDs for the Organization and Person intended for structured data and citations.