Enterprise Knowledge Graph
Connected Intelligence for Strategic Advantage As organizations gather extensive volumes of diverse data across business lines, the opportunity to extract unified understanding grows exponentially. However, information residing in application silos or disconnected systems limits strategic perspective. An enterprise knowledge graph (EKG) addresses this challenge by establishing a virtual intelligence nucleus linking relevant entities and semantics from distributed sources.
01
Entity Linkage
AI algorithms identify and connect related entities like customers, products or assets referenced across diverse sources.
02
Relationship Extraction
Semantic annotations reveal how extracted entities interact based on text, behavioral and event data analysis.
03
Data Discovery
Search and browse graph embeddings to find connected information popular for analytics and system integration needs.
04
Process Automation
Predefined event-based rules trigger actions when graph relationships meet specific conditions.

Intelligent Search

Our intelligent search solutions apply machine learning to index vast semi-structured repositories and surface the most useful information to answer queries.

Computer Vision

By customizing models to your unique content domains, we help organizations harness insights from visual assets to optimize operations, enhance experiences and more.

Recommender System

Our recommender solutions apply machine learning to analyze user behavior and item attributes, delivering individualized suggestions that drive engagement and satisfaction.

Anomaly Detection

Our knowledge graph solutions build contextual taxonomies linking entities across your data ecosystem to power predictive analytics, personalization and more.

Embedded AI

Our embedded AI solutions develop custom machine learning models optimized for deployment on edge devices to power autonomous functionality.

USE CASES 1

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What Are the Advantages You Should Expect?