--- title: About Graph.Build description: A company in London working with data architecture teams inside large organisations. Trading name of Data Lens Labs Ltd, incorporated 2020. --- [Skip to content](https://graph.build/about#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) About # We wanted knowledge graphs to be accessible Everyone who has built one agrees they are worth having and that getting one into production costs more than it should. We spent a long time working out which part of that cost was essential and which part was everybody rewriting the same code. The platform is what came out of the answer. [Book a demo](https://graph.build/enquire/book-a-demo) [Talk to us](https://graph.build/contact) Why we built it ## Ninety per cent of the work was never the model The modelling is the part that needs the experts. It is not the part that takes the time. the finding ### The graph engineering lifecycle Getting a knowledge graph from idea to production took about ten per cent thinking and ninety per cent engineering around the thinking. An ontologist and a subject-matter expert would agree a conceptual model. Then engineers, testers and devops would write a bespoke application to transform the source data into something the model could take, specific to that model and those sources. Then it would be tested, the model would need refining, as models always do, and the whole thing would be written again. The consequence: the cost of a knowledge graph scaled with the number of times you changed your mind, which is a terrible property for something you are trying to get right. studio · entity · Supplier · v14 gbo:Supplier/213847561 hasLegalName Northgate Ltd gbo:Supplier/213847561 rdf:type gbo:Supplier gbo:Supplier/213847561 hasPart gbo:Part/HX-8841 gbo:Part/HX-8841 hasLeadTime 14 (integer) n-triples 8 emitted, validated against supply-chain.ontology all passed unmapped: 0 · quarantined rows keep their reason How it is built ## Three decisions that follow from that Everything opinionated about the platform traces back to the finding above. If iteration is what costs money, then iteration is what has to be free. ### No bespoke ingest code Transformers are configured against the model rather than written against a schema, so refining the model does not mean rewriting an application. Changing your mind costs an afternoon. instead of a rewrite per iteration ### The model is not the database Definitions live in the platform and the database is an output. That keeps the modelling honest. You can shape the model around the domain rather than around what one vendor makes easy. instead of a model shaped by a vendor ### No-code, without a ceiling The people who understand the domain are usually not the people who write the ingest. They should be able to build the model themselves, and the ones who do write code should not be locked out of it. instead of a queue to the data team Customers and partners - ![BT](https://graph.build/hubfs/raw_assets/public/graphbuild-theme/images/partner-bt.png) - ![AWS](https://graph.build/hubfs/raw_assets/public/graphbuild-theme/images/partner-aws.png) - ![Siemens Energy](https://graph.build/hubfs/raw_assets/public/graphbuild-theme/images/partner-siemens-energy.png) - ![Schneider Electric](https://graph.build/hubfs/raw_assets/public/graphbuild-theme/images/partner-schneider-electric.png) - ![Boehringer Ingelheim](https://graph.build/hubfs/raw_assets/public/graphbuild-theme/images/partner-boehringer-ingelheim.png) - ![FS Investments](https://graph.build/hubfs/raw_assets/public/graphbuild-theme/images/partner-fs-investments.png) - ![Ortecha](https://graph.build/hubfs/raw_assets/public/graphbuild-theme/images/partner-ortecha.png) - ![RDFox](https://graph.build/hubfs/raw_assets/public/graphbuild-theme/images/partner-rdfox.png) - ![](https://graph.build/hubfs/raw_assets/public/graphbuild-theme/images/partner-bt.png) - ![](https://graph.build/hubfs/raw_assets/public/graphbuild-theme/images/partner-aws.png) - ![](https://graph.build/hubfs/raw_assets/public/graphbuild-theme/images/partner-siemens-energy.png) - ![](https://graph.build/hubfs/raw_assets/public/graphbuild-theme/images/partner-schneider-electric.png) - ![](https://graph.build/hubfs/raw_assets/public/graphbuild-theme/images/partner-boehringer-ingelheim.png) - ![](https://graph.build/hubfs/raw_assets/public/graphbuild-theme/images/partner-fs-investments.png) - ![](https://graph.build/hubfs/raw_assets/public/graphbuild-theme/images/partner-ortecha.png) - ![](https://graph.build/hubfs/raw_assets/public/graphbuild-theme/images/partner-rdfox.png) The company ## Graph.Build is a trading name of Data Lens Labs Ltd A small company in London, working mostly with data architecture teams inside large organisations. ### Registered in England & Wales Data Lens Labs Ltd, incorporated February 2020 and trading as Graph.Build. Based in London. company no. 12483318 ### Where we work Remote-first across the UK, with delivery alongside your own teams. The platform runs in your infrastructure, so we rarely need to hold your data to help. deployment your account ### Consulting, when it helps Some teams want the platform and nothing else. Others want an ontologist alongside them for the first model. Both are fine, and the second is not a prerequisite for the first. see consulting services ## Bring us the model you have been putting off The interesting conversations start with a domain somebody has already tried to model once. Bring an OWL file, a database schema, or a whiteboard photograph. [Book a demo](https://graph.build/enquire/book-a-demo) [Talk to us](https://graph.build/contact) - 45 minutes, your data, no installation - You keep whatever we model - No obligation to buy anything 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/)