80% of your organisation's data is unstructured, and hence unused.
Take unstructured, raw text data and easily build a knowledge graph that with all detected entities and relationships, and leverage more out of your text. In just a few clicks, with no code involved.
With Standupcode, you can find entities and relationships in unstructured data and automatically enrich your knowledge graph with more information.
While most graphs are built using structured, tabular data, with Standupcode you can go one step ahead and start leveraging the rest of the data in your business.
Use our internal ontology — over 1,000,000 words and concepts about the world — to build your knowledge graph.
Or you can use your own organisation's ontology for more custom use cases. We accept all standard formats.
While we use neo4j to visualise the graph on our platform, you can theoretically use any platform you like — TigerGraph, ArangoDB, MongoDB, Amazon Neptune — we can adapt to you.
We are platform-agnostic. The important thing is your access to your knowledge.
The first step is to import all the your raw text that you want to use to build your graph.
The next step is to import your ontology — including the exact types of relationships and nodes that you want to identify.
We'll then align your ontology with the one we have internally, to make sure that we use the best of both for maximum accuracy.
Finally, we'll build the graph database based on all the information in your raw text.
With graph databases you can gain deeper insight into the relationships between different concepts in your data — see what's connected to what else.
Build more accurate predictive models that use the relationships between different aspects of your data to make decisions and predictions.
The following reviews were collected on our website.
Our Most Frequently Asked Questions