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Graph technology

Solutions

Training

Development

What can graph do for you?

VISUALIZE

Bring your graph data to life in easy to understand visualizations:

  • geospacial and maps
  • dashboards and dependencies
  • KPIs, scoring and segmentation

ANALYZE

Identify patterns and uncover answers informed by your graph data:

  • algorithms
  • anomaly detection
  • relationship mapping

SIMULATE

Conduct "what if" analysis to identify early areas of improvement:

  • "what if" analysis
  • test and save
  • digital twins

OPTIMIZE

Dynamically evaluate between the set of available options:

  • real time
  • intervention
  • better outcomes

How we help clients

Fraud (Anomaly) Detection

  • Path Analysis
  • Graph Embeddings
  • Advanced Visualizations

Custom Training and Support

  • Modeling and Operations
  • Managed Services
  • Tool Specific Training

Customer 360

  • Uniform Customer Model
  • Journey Mapping
  • Visualizations

Secure Graphs - Entitlements

  • Uniform Entitlement Model
  • Entity Resolution
  • Data Ingestion

Rapid Prototypes

  • Business value and ROI creation
  • ROI justification
  • Experience your actual data

Advisory & Implementation

  • Graph Engine Product Selection
  • Integration into the Enterprise
  • Service Enablement

Featured Insights for Graph Technology

BLOG POST

What Machine Learning Can Learn from Graph

Graphs are rich data structures that can be used to improve the accuracy and effectiveness of machine learning workflows.

Graph Demo Gallery

Explore the art of the possible for Graph Technology through Demos, Projects and Webinars.
VIEW GALLERY

With decades of experience in technology innovation, we become true partners with our clients to build what others say can’t be done.

BLOG POST

node classification

by graph convolutional network

DEMO

What are graph databases?

And why should i care?

DEMO

Fraud prevention

For health care

Trending Topics in Graph Technology

training

Introduction to Apache TinkerPop & Gremlin Query Language

This workshop uses TinkerPop Gremlin, and a handful of sample data sets, to teach the Gremlin traversal language through hands-on examples.

Blog

The Three Paradigms of GraphML

The three types of graph machine learning (graphML) are smart data extraction, data structure analysis, and full graphML. This article explains all three.

Demo

Linking Unstructured Data Using Machine Learning

Using unsupervised machine learning, we relate documents together based on their content.

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512.524.7302
Schedule a Meeting
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