Knowledge Graphs

More Clarity, Better Intelligence

Knowledge graphs drive business value by exploiting untapped signals in complex relationships and finding patterns in deeply interconnected, high-dimensional data. A better understanding of data connections and interdependencies enables better decision-making—and graph analytics provides a far greater depth of analysis compared to traditional modeling approaches. Graphs seamlessly connect the dots between disparate data sources and excel when business requirements are dynamic and rapidly evolving. 

Knowledge Management

Real-world data is siloed and lacks standardization. Graphs provide a ‘single source of truth’ for redundant, duplicated data.

Graph Intelligence

Understanding data relationships is often as important as the data itself—and graph-based feature development reveals significant relationships automatically.

Graph Modeling

Graph algorithms automatically develop a larger set of features from a given dataset, making models more accurate and reliable.

What’s Different About Graph Analytics?

Relationships are data: Graphs identify entities that are highly interconnected and belong to similar clusters or communities, pinpointing similarities and shared affinities.

Capture irregular data: Graphs excel at capturing data that is inherently unstructured, high-dimensional, and sparse.

Link to alternative data: Graph networks expect change, so adding new data sources and changing schemas is natural.

Graph Services

  • Customer Experience
  • Patient Journey
  • Electronic Health Records
  • Drug Discovery
  • Fraud Detection
  • Improper Payments
  • Credit Decisioning
  • Entity Resolution
  • Recommendation Engines
  • Targeted Marketing
  • Model Lineage
  • Automated Valuation Models (AVMs)

Is your organization solving hard problems or chasing ambitious goals? We’d love to chat.