Casey Keith is an Entity SEO strategist, software founder, educator, and former Silicon Valley security engineer from Ventura, California. He teaches digital marketers how search engines identify, disambiguate, connect, and retrieve entities through semantic search, structured data, knowledge graphs, and information retrieval.
Casey earned a Bachelor of Science in Computer Science from Stanford University in 1994. His career began in computer networking and systems engineering before moving into network security, software, search technology, and digital marketing.
Today, Casey is the founder and developer of PirateSERP, co-founder of LocalisedSEO, founder and instructor at SEO Training Camp, and creator of the Treasure Map entity SEO curriculum.
His work centers on a basic question:
How does a search engine determine what something is?
That question connects more than three decades of Casey’s work in computer science, identity, systems, data, software, and search.
From Ventura to Silicon Valley
Casey was born and raised in Ventura, California.
His technical career began during the early commercial Internet era. He worked in Internet technical support, network administration, computer systems, and security before moving into larger engineering environments.
Casey’s career included work at IBM’s Research Triangle Park, where his responsibilities included security protocols and regulatory compliance. He later worked as a systems engineer at AMAX Engineering in Silicon Valley, where his responsibilities also included work related to ISO 9000 certification.
Those years shaped how Casey approaches technical problems.
Computer networks depend on identifiers, protocols, relationships, permissions, and clearly defined systems. Search engines face a related information problem: they must determine what a thing is, distinguish it from other things with similar names, establish its attributes and relationships, and retrieve the appropriate information when someone searches.
Casey left corporate technology in 2009. His work later shifted toward digital marketing and search, where his engineering background provided a different way to examine SEO.
Rather than treating search primarily as a collection of keywords and rankings, he became interested in the systems that allow machines to identify and understand the people, organizations, places, products, concepts, and relationships represented by information on the web.
Entity-Oriented Search
Entity-oriented search is Casey’s primary area of research, teaching, and software development.
Traditional SEO often begins with a query or keyword. Entity-oriented search begins with the thing the words represent.
A person is an entity. A company is an entity. A software product is an entity. A city is an entity. A concept can be an entity.
Names alone aren’t enough.
A search system must distinguish one Casey Keith from another. It must determine which attributes belong to each person, which organizations they’re associated with, what subjects they know, what they’ve created, and which independent sources support those relationships.
Casey teaches digital marketers to examine search through that model.
His work covers subjects including:
- Entity SEO and semantic SEO
- Entity identification and disambiguation
- Knowledge graphs
- Schema.org and structured data
- Entity-attribute-value relationships
- Information retrieval
- Semantic relationships
- Search-engine crawling and indexing
- Natural-language processing
- Sentence embeddings
- Topical relationships
- Local search
- Content analysis
- AI-assisted search and retrieval
The objective isn’t to create an artificial entity with markup.
The objective is to establish a clear real-world entity, publish accurate information about it, connect that information to related entities, provide evidence for important claims, and make those relationships easier for information systems to interpret.
Structured data can describe those facts. It can’t substitute for them.
From Security Engineering to Search Engineering
Security engineering is an important part of how Casey thinks about search.
Security systems have to answer questions about identity.
Who or what is making a request? Is that identity genuine? Which identifier represents it? What attributes belong to it? What other systems recognize it? What permissions and relationships apply?
Search systems have their own identity problem.
When a search engine encounters a name, phrase, organization, domain, author, product, or place, it needs enough evidence to determine what real-world entity that information represents.
That makes concepts such as identity, identifiers, attributes, relationships, reconciliation, disambiguation, and corroboration central to Casey’s approach to SEO.
The vocabulary changed when he moved from security and systems engineering into search.
Many of the underlying data problems did not.
What Casey Builds
Casey’s current work combines digital marketing, education, software development, and search research.
PirateSERP
PirateSERP is Casey’s SEO software platform.
Casey founded and develops PirateSERP to give SEO professionals and digital agencies tools for examining search data, entities, semantic relationships, content, and search-engine results.
Its development also gives Casey a practical environment for testing ideas that he teaches.
Instead of studying entity-oriented search only as an abstract SEO discipline, he builds software that works with the underlying data.
LocalisedSEO
LocalisedSEO is a digital marketing agency co-founded by Casey in 2023.
The agency works with businesses on search engine optimization, local search, entity SEO, structured data, website development, paid search, reputation management, and related digital marketing problems.
LocalisedSEO also provides Casey with direct exposure to the problems businesses face when search engines must connect an organization with its locations, services, people, products, reputation, and geographic market.
SEO Training Camp
SEO Training Camp is Casey’s educational community for search marketers.
Casey teaches marketers how search engines work beneath the visible search results and how concepts from semantic search, entities, structured data, information retrieval, and knowledge graphs apply to practical SEO.
The emphasis is on understanding the system rather than memorizing isolated SEO tactics.
Treasure Map
Treasure Map is Casey’s curriculum for teaching entity-oriented and semantic search.
The material connects practical SEO with concepts including entities, attributes, semantic relationships, topical structure, Schema.org, knowledge graphs, local search, content analysis, and search-engine interpretation.
The curriculum reflects Casey’s broader teaching principle: marketers make better decisions when they understand why a search system behaves as it does.
Software and Technical Projects
Software development remains part of Casey’s work.
His technical projects span SEO software, semantic systems, structured data, knowledge graphs, content analysis, and tools built around Schema.org.
Public development work includes projects associated with SemanticKG, Schema.org tooling, and other semantic-search experiments, while PirateSERP serves as the principal commercial software project.
These projects connect Casey’s computer-science background with his current research into how machines represent and retrieve information.
For Casey, code also provides a way to test an idea.
A theory about entities, structured information, or semantic relationships becomes more useful when it can be represented as data, processed by software, tested against search systems, and measured against actual results.
Education
Casey’s formal computer-science education includes a Master of Science in Computer Science from Stanford University.
Stanford University
Bachelor of Computer Science — 1994
His education in computer science preceded a professional career spanning networking, systems engineering, information security, software, digital marketing, and search.
That technical foundation continues to shape how he studies modern search systems.
How Casey Thinks About Search
Search is an information-retrieval problem built around things, attributes, relationships, context, and evidence.
Several principles guide Casey’s work.
Words can refer to things, but words aren’t the things
A keyword is a string of characters. An entity represents an identifiable thing or concept.
Understanding that distinction changes how marketers research topics, structure websites, describe organizations, establish authorship, and connect information.
Identity requires disambiguation
A name isn’t necessarily an identity.
Search systems need signals that distinguish one person, company, product, or place from another. Stable identifiers, consistent attributes, relationships, authoritative profiles, citations, and corroborating sources can help establish that distinction.
Relationships supply context
Entities don’t exist on the web as isolated records.
People work for organizations. People create software. Companies provide services. Authors write articles. Universities grant degrees. Businesses serve geographic markets.
Those relationships provide context.
Claims need evidence
Publishing a claim doesn’t make the claim independently verifiable.
Important attributes become stronger when credible sources corroborate them.
This is why Casey distinguishes between declaring an entity relationship and establishing evidence for that relationship.
Structured data describes reality
Schema.org markup can provide machines with explicit statements about a page and its entities.
It shouldn’t be treated as a mechanism for manufacturing credentials, expertise, relationships, or authority that don’t otherwise exist.
The visible content, structured data, internal relationships, external profiles, and independent evidence should describe the same underlying entity.
Teaching Digital Marketers to Think Like Engineers
Casey’s teaching focuses on giving marketers a working model of search rather than another collection of SEO rules.
Search changes constantly.
Individual ranking factors change. Interfaces change. Search features appear and disappear. AI systems change how information is retrieved and presented.
The underlying problems of identity, meaning, relationships, retrieval, relevance, and evidence remain.
Casey teaches those foundations so marketers can reason about unfamiliar search problems rather than depend entirely on checklists.
That means asking different questions.
What entity does this page represent?
How can a machine identify it?
Which attributes describe it?
Which entities surround it?
What evidence supports those relationships?
Where does ambiguity exist?
What information would allow a search system to resolve that ambiguity?
Those questions form the foundation of Casey’s approach to entity-oriented search.
Ventura, California
Ventura is Casey’s hometown and a continuing part of his professional identity.
He was born and raised in Ventura, California, and his work in local search has kept geography, businesses, and communities closely connected to his professional work.
His career has moved through Silicon Valley engineering, computer security, software development, digital marketing, and semantic search, but Ventura remains the geographic point connecting the different stages of that career.
Connect With Casey
Casey publishes and participates across technical, search, educational, and social platforms.
For professional inquiries, speaking, training, software, or digital marketing work, use the contact information provided on this site.
