In AI Search, Trust isn’t Random. It’s engineered.
Build an Unbreakable Foundation of Authority
Trust Stack™ combines every critical trust signal into a single system—positioning your brand as the verified source AI systems choose to trust.
DEEP TECH EXPERIENCE | 15+ YEAR TRACK RECORD | AI EXPERTISE
One Seamless Trust Blueprint Built for Answer Engines
We create and deploy the digital trust assets your company needs to attract AI retrievers, in one unified system.
Structured Data Buildout
Blueprint your site for machine understanding.
Give AI crawlers a precise map of your brand's credibility by embedding structured data across your entire digital footprint. Amplify visibility in rich results and knowledge panels, ensuring your content gets cited and chosen over competitors.
Knowledge Graph Optimization
Plant your flag in AI’s go-to source for truth.
Plant your brand inside AI’s structured understanding of the world by claiming and optimizing your Knowledge Graph presence. Establish a durable entity identity that AI retrievers instantly recognize and trust.
Author and Entity Verification
Link your real-world identity to your digital presence.
Authenticate the real-world identities behind your content through structured verification frameworks. Verified entities are prioritized by AI retrievers as credible, reliable sources of truth.
Ontology & Governance
Turn your brand story into an asset, not a rumor mill.
We build your domain ontology, claims registry, and change controls so LLMs see one canonical truth—complete with IDs, provenance, and versioning. This is Layer 0 of Trust Stack™.
Trust Signals That Don’t Just Help, They Compound
Trust Stack™ is a compounding visibility process that positions your company as the source that ChatGPT cites, Claude highlights, and buyers turn to first.
Enhance Long-Term Visibility
Trust Stack™ creates a durable foundation of trust signals that compound over time, helping your brand stay resilient as AI search evolves.
Strengthen Your Citation Credibility
By layering authoritative signals, Trust Stack™ increases the likelihood that AI models will select and recognize your content as a trusted source.
A Single Source of Truth for AI Models
Canonical IDs, consistent vocabularies, and change control is the secret to helping AI reliably attribute citations to your brand.
Safeguard Against Costly Hallucinations
When AI models attribute your content as a trusted source, buyers arrive pre-sold on your expertise.
READY TO 10x AI-NATIVE GROWTH?
Stop Guessing and Start Optimizing for AI Search
Or → Start Turning Prompts into Pipeline!
Trust is the New Armor
Leverage an integrated system of structured data, authoritative citations, verified entities, and embedded trust signals, engineered to feed hungry AI models exactly what they’re looking for.
Trust Stack: Your Strongest AI Search Advantage
Trust Stack is a precision-built framework designed to inject your brand into the knowledge graph, align your digital footprint with AI retrievers, and ensure you don’t just rank, you get surfaced, cited, and chosen. It weaves structured data, entity verification, citations, and trust signals into one system—built to supply AI models with exactly the context they reward.
Aggregate brand trust signals for AI authority:
Ontology & Governance — Adapt to the structure and rules that keep AI Search ecosystems coherent, ensuring entities, relationships, and updates are consistently defined, managed, and trusted.
Knowledge Graph Optimization — Align entities, attributes, and relationships into a machine-readable network, making your brand’s information easier for AI systems to retrieve, connect, and cite.
Structured Data Buildout — Translate your content into precise schema markup, giving AI systems explicit signals that boost visibility, context, and citation accuracy.
Author Verification — Establish a provable link between content and its creator, strengthening trust, credibility, and attribution in AI search.
Trust Stack™ is our proprietary framework for building layered credibility signals—identity, authority, and provenance—that make AI systems more likely to surface and cite your brand.
Why Work With Growth Marshal
Aside from our good looks and sharp wit, founders hire us because we're at the frontier of AI Search—launching you into an unfair lead on the new track of startup growth.
AI-Native Search Masters
We don’t just optimize for Google—we engineer your brand into the very fabric of LLM retrieval. From knowledge graph tuning to zero-click authority, we make sure AI cites you, not your competitors.
AI-First, Results-Obsessed
You move at AI speed; so do we. Our entire system is built for compounding returns—quick wins today and scalable gains tomorrow, without the bloat of legacy agency processes.
Data-Backed, Always
Every recommendation is rooted in proprietary research, real-world embedding tests, and hard performance data. You’ll see exactly which signals move the needle—and we’ll double-down on the ones that do.
Full-Spectrum Service Suite
From prompt surface engineering to hallucination monitoring, we cover the entire AI-SEO lifecycle. No handoffs between siloed groups—just one integrated team driving your discovery and citation.
High-Octane Partnership
We speak startup fluently: sharp insights, zero fluff, and a relentless drive to turn your company into a lead-generation machine. Expect candid feedback, rapid pivots, and messaging that cuts through the noise.
READY TO 10x AI-NATIVE GROWTH?
Stop Guessing and Start Optimizing for AI Search
Or → Start Turning Prompts into Pipeline!
Trust Stack™ FAQs
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Trust Stack™ embeds your brand into the retrieval layer by unifying structured data, verified authorship, and third-party validation—signals modern LLMs and search engines prefer when selecting trustworthy sources.
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Growth Marshal delivers a single system that includes Structured Data Buildout, Knowledge Graph Optimization, Author & Entity Verification, and Ontology & Governance, so your brand presents one canonical truth across the semantic web.
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AI algorithms prioritize verifiable signals—structured data, linked entities, and authoritative citations—over keyword volume; unverifiable content is filtered out automatically.
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You can earn visibility in featured snippets, knowledge panels, and LLM answers, drive higher click-through from credibility signals, stay resilient through algorithm/model shifts, and shorten sales cycles with lower CAC.
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Traditional SEO focuses on content and backlinks; Trust Stack™ goes deeper by aligning entities and provenance (schema, knowledge graph, verification, third-party credibility) so your brand gets retrieved, cited, and trusted.
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It’s built for startups, small businesses, and even solopreneurs. It can be adapted to pre-seed through Series B+ to establish durable authority in LLMs.
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It’s the foundation that codifies your domain entities, claims registry, IDs, provenance, and change controls so LLMs see one canonical, versioned source of truth.
Terminology
A reference guide to our funky nomenclature and proprietary frameworks.
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AI-Native Search is a search paradigm where large language models and answer engines assemble answers and cite sources, not just rank links.
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An AI Retriever is the component of an AI system that selects sources/entities to ground responses and citations.
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A Structured Data Buildout is an end-to-end schema deployment that makes brand facts machine-readable and eligible for rich results and knowledge panels.
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Knowledge Graph Optimization means aligning your entity, attributes, and relationships so AI recognizes a durable, trustworthy identity.
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Author & Entity Verification refers to the need to prove real-world identity behind content so as to raise credibility with retrieval systems.
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Ontology refers to your domain’s formal vocabulary—entities, relationships, and definitions—plus the rules that keep them consistent for AI.
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Within the context of AI Search, Governance means versioned policies and workflows that manage updates to facts and taxonomy so one canonical truth persists.
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A Canonical ID is a stable, unique identifier for an entity used across content and data layers to unify references and attribution.
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Within the context of Generative Engine Optimization, Provenance & Versioning refer to source trails and timestamps that show where a fact came from and how it changed, improving AI trust.
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Within AI Search, a Single Source of Truth is the consolidated, canonical record—IDs, vocabulary, and controls—that AI models should treat as authoritative.
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An AI Citation is when retrieval-based systems (e.g., GPT, Perplexity, Claude) select and attribute your content as the supporting source.
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A (model) Hallucination is an invented or misattributed answer; mitigated by canonical IDs, consistent vocabularies, and governance.