Hey folks, we’ve open sourced a python library we built at Vouch Insurance to manage our knowledge graph and transform tabular data into RDF.
You might remember us from KGC’22, where we gave a talk on “Modeling the startup ecosystem using a config-based knowledge graph.”
You can check out Quadipy in Github or read our release blog post over here. Looking forward to seeing folks use this!
What are some tools you have used before to successfully profile and optimize SPARQL queries? We’re using Neptune, and hoping to measure where our bottlenecks are.
cc nabeel, Ora L.
My team at Vouch is hiring a Senior Data Engineer and a Machine Learning Engineer to help us build a knowledge graph to understand risk in the startup/venture ecosystem. We’re an insurance tech startup building commercial insurance products for other early stage companies.
Come to our talk Modeling The Startup Ecosystem Using A Config-Based KG tomorrow at 10am in Room 3/Classroom B to learn more about what we’re building, or find me and nabeel in person if you’re at the conference!