Why Graph Data Embeddings

Graph data embeddings allow us automate the analysis of complex and critical systems using real-world interconnected data.

This exciting AI solution unlocks possibilities in how we leverage social networks, media, publication data, information from life sciences and geography and more. With graph data embeddings, we can capture additional information often lost in relational systems.

Typical problems

People don’t typically know how to deploy graph systems and instead deploy machine learning within tabular datasets.

Increasingly available (and useful) graph databases are not tabular. Turnkey machine learning solutions can’t help companies looking to leverage complex, related data. Often the expertise needed to identify and deploy graph data embeddings aren’t available within the organization. 

How we help

Synaptiq partners with clients to identify and deploy an optimal graph data embedding solution.

We are only starting to unlock possibilities hidden in graph data. Some interesting ways we have helped clients include,

    • Leveraging social graphs to connect people in a social network
    • Architecting security graphs for pinpointing where anomalies occur and how they spread through systems, networks, etc.
    • Using supply chain graphs to understand the flow of information and products and optimize cost, time, and other factors

Who benefits

Many different kinds of companies can use graph data embeddings to improve the work they do and offer innovative solutions.

Some sectors we have helped are below but our recent white paper offers some ideas for how we can help other clients unlock the potential hiding in their data. 

    • Healthcare
    • Cybersecurity
    • High tech 
    • Geospatial 

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About Us

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