For enterprises building with knowledge graphs

Production knowledge graphs,
end to end.

From ontology to cloud infrastructure, Graphweave builds the semantic systems your domain experts actually use. Work delivered at IKEA, Siemens Energy, and the European Union Agency for Railways.

Work delivered at

Organizations running Graphweave work in production

IKEA
Siemens Energy
European Union Agency for Railways
What we do

Three things, done well.

Vertical integration from ontology through cloud. One practice, not four handoffs.

Production knowledge graphs

Ontology design, SPARQL, triplestore selection, deployment. The plumbing that has to work: RDF, OWL, SHACL, reasoning, federation, and the pipelines that keep the graph fresh.

Semantic applications for domain experts

User-facing tools built on top of knowledge graphs. Typically Metaphactory, but custom stacks too. The pattern we shipped for IKEA and Siemens Energy: the people who own the data also own the application.

Platform rescue and rearchitecture

Taking over struggling or unmaintainable semantic systems and making them production-ready. Migrations, rewrites, infrastructure untangling. The pattern behind the ERA RINF rearchitecture.

Supporting capabilities: Collibra integration, SPARQL federation, AWS and Azure infrastructure for semantic systems.

Case studies

Production work, not slides.

Three engagements that cover the full Graphweave stance: ontology, application, and infrastructure.

IKEA

Real-time reasoning for the IKEA Knowledge Graph

Problem

Cross-product relationships (add-on recommendations, compatibility, substitutions) were being curated manually, article by article. The process did not scale to the catalog, and the domain experts closest to the data had no way to express relationships as rules.

Approach

Built a reasoning application on RDFox Datalog and Metaphactory that lets home-furnishing knowledge engineers author cross-product relationships as declarative rules. Each rule generates thousands of pairings automatically. Rearchitected the Databricks pipeline so the domain team contributes directly to the KG, with validation errors surfaced back to the authors. Delivered the ontology, mappings, and the Azure platform underneath.

Outcome

Manual article-by-article curation replaced with rule-based authoring controlled by the people who own the domain. Thousands of product pairings produced per rule, driving measurable lift in online conversion.

RDFoxDatalogMetaphactorySPARQLSHACLRDFOWLDatabricksAzure
Siemens Energy

Domain Ontology Editor for engineering catalog management

Problem

Millions of engineering catalog terms needed curation by engineers across the business, with full versioning and auditability. The existing tooling did not give domain teams a safe way to edit taxonomies, and there was no way to see how the catalog had looked at a given point in time.

Approach

Designed and built an internal Metaphactory-based application, acting as sole developer and maintainer. Shipped a custom enumeration editor and a time-machine interface that lets engineers browse any historical state of the catalog. Lineage and auditability are modeled on PROV-O. Also owned the supporting AWS infrastructure end to end: Collibra on EKS, deployments via AWS CDK and Terraform, and resolution of cross-team issues (Graviton RDS migration, Terraform and EKS version drift, Route 53 and ALB DNS misconfigurations).

Outcome

Domain engineers curate a catalog at the scale of millions of terms, with a navigable history and full provenance. One integrated system where there used to be several.

MetaphactorySPARQLPROV-OCollibraAWSEKSCDKTerraform
European Union Agency for Railways

RINF rearchitecture (Register of Infrastructure)

Problem

RINF is the EU-wide regulatory system tracking rail infrastructure across every member state. The platform had grown into a tangled set of microservices that the agency could no longer evolve internally, and its semantic transformation pipeline was too slow to keep up with member-state submissions.

Approach

First deployed the legacy version to production, then led the full rearchitecture: replaced the microservice tangle with a modular FastAPI application on EKS Fargate. Rebuilt the semantic transformation pipeline from scratch in Python on an asynchronous Celery and SQS architecture. Owned authentication and authorization end to end via Azure Active Directory.

Outcome

50x speedup on the semantic transformation pipeline. A maintainable codebase the agency can evolve internally, running EU regulatory infrastructure in production.

PythonFastAPIEKS FargateAzure ADCeleryAmazon SQSSPARQLRDF
How we build

Platforms and technologies

The stack Graphweave has shipped in production for enterprise clients. Platform-agnostic in principle, opinionated in practice.

Semantic & knowledge graph

RDFOWLSPARQLSHACLPROV-ODatalogRDFoxGraphDBMetaphactoryCollibra

Platform & data

AWSAzureEKSFargateAWS CDKTerraformDatabricksPythonFastAPICeleryAmazon SQSAzure Active Directory
About

Founder-led,
built to scale carefully.

Graphweave is a specialist consultancy for enterprise knowledge graphs, led by founder Christos Papacharalampous.

Christos has spent the past three years as a senior freelance knowledge graph engineer for IKEA, Siemens Energy, and the European Union Agency for Railways, building production semantic systems end to end: from ontology modeling and SPARQL through to the applications domain experts use and the cloud infrastructure that keeps them running.

Graphweave exists to scale that practice without diluting it. A boutique consultancy, currently one principal, growing deliberately.

Millions
In incremental revenue from the IKEA Knowledge Graph reasoning engine
50×
Pipeline speedup for the EU rail infrastructure regulator (ERA)
Millions
Engineering catalog terms curated at Siemens Energy
End to end
Ontology, application, and cloud, shipped as one practice
Contact

Let's talk shop.

Exploring a knowledge graph project, inheriting a semantic system that needs rescuing, or just want to compare notes? Drop a line.

Free architecture health check

Not sure where to start? Describe your current semantic stack in the form below: the triplestore, the pipeline, what hurts. You get a short written assessment of the biggest risks and the quickest wins across modeling, queries, pipelines, and infrastructure. No sales deck, no call required, no obligation.

Graphweave is certified by EUROCERT to ISO/IEC 27001, ISO/IEC 27701, and ISO 9001. What you share is handled under audited security and privacy controls.

Based in Thessaloniki, working remotely across Europe.