--- title: Knowledge Graph and Graph Database Consulting Services description: The team have been working in the knowledge graph space for over 10 years providing services to companies whatever their stage of knowledge graph adoption. --- [Skip to content](https://graph.build/consulting-services#main) [![graph.build](https://graph.build/hubfs/raw_assets/public/graphbuild-theme/images/logo-secondary-reverse.svg)](https://graph.build/) Menu - Platform - AI context [Context for AI](https://graph.build/ai-context) [Semantic layer](https://graph.build/semantic-layer) [GraphRAG](https://graph.build/graphrag) [MCP & agent access](https://graph.build/mcp) [Ontologies explained](https://graph.build/resources/ontology) - Resources [Blog](https://graph.build/blog) [Graph fundamentals](https://graph.build/resources) [Documentation](https://graph.build/documentation) - Company [About us](https://graph.build/about) [Consulting](https://graph.build/consulting-services) [Contact](https://graph.build/contact) [Book a demo](https://graph.build/enquire/book-a-demo) Model [Studio](https://graph.build/graph-build-studio) [Visual graph modelling](https://graph.build/graph-modelling-tool) [Ontologies & vocabularies](https://graph.build/platform-architecture#ontology) Transform [Transformers](https://graph.build/graph-build-transformers) [Knowledge graph ETL](https://graph.build/knowledge-graph-etl) [Change data capture](https://graph.build/graph-build-transformers#cdc) Write [Writers](https://graph.build/graph-build-writer) [Database compatibility](https://graph.build/graph-databases) [Deployment](https://graph.build/platform-architecture#deployment) You are here [The graph engineering lifecycle](https://graph.build/knowledge-graph-building) Design, configure, engineer, iterate and automate graph model production: the whole lifecycle, without writing bespoke ingest code for each project. Model [Studio](https://graph.build/graph-build-studio) [Visual graph modelling](https://graph.build/graph-modelling-tool) [Ontologies & vocabularies](https://graph.build/platform-architecture#ontology) Transform [Transformers](https://graph.build/graph-build-transformers) [Knowledge graph ETL](https://graph.build/knowledge-graph-etl) [Change data capture](https://graph.build/graph-build-transformers#cdc) Write [Writers](https://graph.build/graph-build-writer) [Database compatibility](https://graph.build/graph-databases) [Deployment](https://graph.build/platform-architecture#deployment) AI context [Context for AI](https://graph.build/ai-context) [Semantic layer](https://graph.build/semantic-layer) [GraphRAG](https://graph.build/graphrag) [MCP & agent access](https://graph.build/mcp) [Ontologies explained](https://graph.build/resources/ontology) Resources [Blog](https://graph.build/blog) [Graph fundamentals](https://graph.build/resources) [Documentation](https://graph.build/documentation) Company [About us](https://graph.build/about) [Consulting](https://graph.build/consulting-services) [Contact](https://graph.build/contact) [Book a demo](https://graph.build/enquire/book-a-demo) Consulting # Fourteen years of knowledge graphs, before there was a platform to sell you We built Graph.Build because we kept doing the same engineering by hand. The people who wrote it still take on the work it came from, mostly when a team wants an ontologist alongside them for the first model rather than a tool and good luck. [Start a conversation](https://graph.build/consulting-services#enquiry) [See the platform](https://graph.build/platform-architecture) What we are brought in for ## Six things, and the first one decides the other five Almost every engagement starts with a model somebody has already attempted. The rest follows from getting that right. ### Ontology and data modelling The part that needs the experts and repays the time. A model that describes the domain rather than the schema of whichever system got there first. Pragmatic, published, and something the people who own the domain can read. output an OWL model you keep ### Linking data across internal systems Large organisations describe the same thing four different ways in four different databases. Reconciling those into one model is most of the work in most projects, and it is work we have done in enough industries to recognise the patterns. typical scope 4 to 12 sources ### Open data integration There is a large and growing world of public data. Linking your domain to DBpedia, Wikidata, GeoNames and the rest enriches what you already hold, which shows up in annotation, search and anything you build on top. sources public and licensed ### Content and document extraction Making unstructured documents findable by pulling concepts out of them and linking them to the graph. Known concepts and unknown ones, so the model grows from what the corpus actually contains. related the Document Transformer ### Semantic publishing We have helped build some of the largest digital publishing platforms in the world. Tagging assets with real concepts rather than free-text keywords is what makes automatic linking, data-driven pages and useful search possible at all. sectors publishing and media ### Content platforms that are data driven Off-the-shelf content systems assume a page is the unit. When the unit is a concept, you need something else. We have built these before and will reuse what we have rather than starting from a blank repository. approach reuse, then build Where we have done it ## Regulated, published, engineered The industries differ. The problem underneath them rarely does. ### Industries Pharmaceuticals, life sciences, finance, engineering, e-commerce, publishing and media. Enough regulated ones that provenance and audit are not new requirements to us. since 2015 ### Clients From small companies with one product to organisations where the data architecture team is larger than most companies. Engagements are scoped to match, and a first one is usually small on purpose. shape alongside your team ### What you are left with A model, the mappings that fill it, and people on your side who can change both. If the engagement ends and nothing can be altered without us, it did not work. ownership yours Before you ask ## The four questions that come up on the first call [Ask us a fifth](https://graph.build/contact) Do we have to buy the platform to work with you? No. Consulting and the platform are sold separately and a good number of engagements have been modelling work with no software in them at all. The reverse is also true: most people who license the platform never speak to us beyond support. Who owns the model at the end? You do. It is an OWL or RDFS file and it is yours, along with the mappings. That matters more than it sounds: an ontology you cannot take with you is a dependency dressed as a deliverable. Do you work on your own or with our team? With your team, and deliberately. The subject-matter experts are on your side and the point of the engagement is that they end up able to do this without us. We are usually a small number of people working alongside a larger number of yours. How does an engagement usually start? With a domain someone has already tried to model once and a conversation about why it stalled. That is enough to say whether this is a week of modelling, a first project, or something you do not need us for. We would rather say the last one early. Consulting enquiry ## Bring us the model you have been putting off Tell us what you are trying to describe and what has stopped you so far. That is usually enough for a useful first answer. - A reply from someone who does the work, not a qualification call - We will say if you do not need us - Nothing you send is shared outside the team typical reply one working day first session 45 minutes, no charge based London consulting enquiry name, email, what you are modelling Goes to the consulting team. Not added to any marketing list unless you ask. Platform [Studio](https://graph.build/graph-build-studio) [Transformers](https://graph.build/graph-build-transformers) [Writers](https://graph.build/graph-build-writer) [Database compatibility](https://graph.build/graph-databases) [Platform architecture](https://graph.build/platform-architecture) AI context [Context for AI](https://graph.build/ai-context) [Semantic layer](https://graph.build/semantic-layer) [GraphRAG](https://graph.build/graphrag) [MCP & agent access](https://graph.build/mcp) [Ontologies explained](https://graph.build/resources/ontology) Resources [Blog](https://graph.build/blog) [Graph fundamentals](https://graph.build/resources) [Choosing a graph database](https://graph.build/graph-databases) [How to build a knowledge graph](https://graph.build/knowledge-graph-building) [Documentation](https://graph.build/documentation) Company [About us](https://graph.build/about) [Consulting](https://graph.build/consulting-services) [Contact](https://graph.build/contact) Legal [Privacy policy](https://graph.build/privacy-policy) Get in touch No newsletter. If you want to talk about a model, or want to be kept posted, the contact form is the way in. [Contact us](https://graph.build/contact) - © 2026 Graph.Build · A trading name of Data Lens Labs Ltd, registered in England & Wales, company number 12483318 [![graph.build](https://graph.build/hubfs/raw_assets/public/graphbuild-theme/images/logo-secondary-reverse.svg)](https://graph.build/) ```json { "@context" : "http://schema.org", "@type" : "Service", "areaServed" : { "@type" : "", "name" : "" }, "hasOfferCatalog" : { "@type" : "OfferCatalog", "itemListElement" : [ ], "name" : "Knowledge Graph Consulting" }, "provider" : { "@type" : "LocalBusiness", "address" : { "@type" : "PostalAddress", "addressCountry" : "UK", "addressLocality" : "Twickenham", "addressRegion" : "England", "postalCode" : "TW1 3HX", "streetAddress" : "47 Beaconsfield Road" }, "image" : [ "https://graph.build/hubfs/graph-build-logo-primary.svg" ], "name" : "Graph.Build", "priceRange" : "£800 per Day", "telephone" : "" }, "serviceType" : "Knowledge Graph Consulting" } ```