Name: KGNN
Author: Equitus

Customer Training

Help Desk

Web and Video Conferencing

Customer Support

Batch Management Software

Functional Testing

Development

Business Intelligence (BI)

Collaboration

Data Extraction

Dropshipping

Emissions Management

Intellectual Property (IP) Management

Privacy Policy Generators

Statistical Analysis

Workflow

Enterprise

Accounting

Accounts Payable

Crypto Tax

Online Trading

Subscription Management

Treasury Management

Finance and Accounting

Applicant Tracking

Corporate Learning Management

HR Compliance

HR Management

Payroll

Relocation

Talent Intelligence

Talent Management

Workforce Analytics

Workforce Management

Human Resources

AI Agent Builder

AI Governance

Authorization

Cloud Storage

Custom Software Development Services

Data Center Virtualization

DevSecOps

Fraud Detection

Infrastructure-as-Code (IaC)

Integration Platform as a Service (iPaaS)

Managed Public Cloud Infrastructure

Network Performance Monitoring

Secure Email Gateway

Sensitive Data Discovery

Session Border Controllers

System Monitoring

Time Series Databases

Tower Servers

Web Portal

Information Technology

A/B Testing

AI Image Generation

Ad Serving & Retargeting

All-in-One Marketing

Audience Engagement

Content Management

Email Marketing

Market Intelligence

Marketing Automation

Social Media Advertising

Social Media Management

Survey & Forms Building

Web Analytics

Marketing

Project Management

Professional Services

Customer Relationship Management (CRM)

Lead Generation

Lead-to-Account Matching and Routing

Sales Enablement

Sales

Cloud Infrastructure Entitlement Management

Secure Service Edge (SSE)

Security

Architecture

Banking

Digital Forensics

Financial Services CRM

Internet of Medical Things

Vertical-Specific

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KGNN

Knowledge Management

Equitus KGNN Demo Introduction

KGNN displaying a richly connected semantic network generated by Equitus KGNN. At the center is a core entity node, automatically linked to multiple other entity types such as people, organizations, locations, and categories. These nodes are color-coded and icon-tagged to represent different entity classes.

an image where the user is selecting from a variety of layout modes, Concentric, Lens, Sequential, Organic, and Structural, each offering different visual perspectives to better understand the graph’s structure. The central workspace displays a dynamically generated graph consisting of nodes (entities) and links (relationships), color-coded by type or category. Users can manipulate the graph view, search items, group nodes, add documents, run queries, or export the graph data for further analysis.

Equitus's integrated UI, which is designed to visualize and interact with the knowledge graph automatically generated by KGNN. The interfae is not required for KGNN to function but offers a powerful, intuitive environment for users who wish to explore and validate semantic relationships within the graph.

the interface that enhances transparency and usability of the knowledge graph, especially in environments where data traceability, context validation, or manual exploration is necessary.

Equitus

KGNN Knowledge Graph Neural Network - Automated Knowledge Engine for Enhanced AI Reasoning Brochure

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KGNN

Overview

What is KGNN?