Lettria Knowledge Studio

Turn Unstructured Text into a Graph

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.

Lettria's structuration model

Discover how AP-HP turned patient data into a goldmine of information

How AP-HP uses knowledge graphs to structure patient data

Build and enrich your knowledge graph.

With Lettria, 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 Lettria you can go one step ahead and start leveraging the rest of the data in your business.

Use Lettria's highly developed ontology, or use your own.

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.

Read more about our knowledge management tools →

Use the Graph DB that works for you.

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.

Your text made into a graph, step by step:

Here's what we offer in four steps:

1. Raw text import

The first step is to import all the your raw text that you want to use to build your graph.

2. Ontology import

The next step is to import your ontology — including the exact types of relationships and nodes that you want to identify.

3. Ontology alignment

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.

4. Text to graph processing

Finally, we'll build the graph database based on all the information in your raw text.

What can you use graph databases for?

Tap into relationships between your data

With graph databases you can gain deeper insight into the relationships between different concepts in your data — see what's connected to what else.

Make higher quality data-driven decisions

Build more accurate predictive models that use the relationships between different aspects of your data to make decisions and predictions.

See our text to graph demo in action

We've built a text to graph demo that's already live on our platform.
Here's what it looks like.

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Lettria Knowledge Studio
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