Linking Business to Data

We deliver a highly scalable and reliable Linked Data infrastructure.
You can focus on extracting value from it

Contact Us

Take control over your data today

Open and Closed

You decide whether your data is published publicly or privately. Triply comes with an easy to configure management console that lets you specify read/write permissions.

Quality Control

Triply builds on the award-winning LOD Laundromat system to ensure that all your data is standards-compliant and meets the latest quality criteria.

Data Versioning

Triply keeps track of multiple versions of your data. Every version can be queried and all versioning information is stored as queryable Linked Data.

Low Entry Level

With APIs for JavaScript, .Net and Java, Triply does not require experience with Linked Data technology. For the Semantic Web literatre, Triply supports the standard Linked Data APIs as well.


With Triply your Linked Data API is guaranteed to have very high availability. Your API will always work, even under intensive data use.


Triply puts no fixed limit on the size of your data. It does not matter whether you have 10 or 10,000,000,000 statements.

Start extracting value from your data

Triply is founded by Laurens Rietveld and Wouter Beek

Laurens is specialized in Web Engineering and large-scale Infrastructure Deployment. He obtained his PhD on scalable Linked Data solutions under the supervision of Frank van Harmelen. Laurens has built the most popular SPARQL editor YASGUI. He has also been responsible for the technical ecosystem surrounding the LOD Laundromat and has previously worked as Software Engineer at GfK.

Wouter is PhD researcher at VU University Amsterdam. He has built the award-winning LOD Laundromat together with Laurens, which has won both the Best Paper Award (ISWC) and the Best LOD Application Award in 2015. His current research is about applying Knowledge Representation techniques to very large data collections such as the Semantic Web. He is working together with Frank van Harmelen in the KR&R research group.