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Enterprise

Enterprise Operating Intelligence

Enterprise intelligence connecting business operations

From Fragmented Data
to Trusted Enterprise Operations

Transforming scattered data into trusted enterprise operations

By connecting enterprise operational data and digital assets with supply chain and cyber threat information into a single context, we advance decision-making and risk response in complex enterprise environments.

Market Dynamics & Trends

Enterprise Intelligence
Under AI and Cyber Complexity

The enterprise operating environment in an era of AI expansion and cyber risk

Cyber Security
ISSUE

The spread of hybrid and multi-cloud environments and the limits of asset visibility

- as visibility into assets and privileges declines in environments where on-premises and multi-cloud are mixed, delays in breach detection and The risk of long-term dormancy are increasing.

Average time to resolve a breach

41 days

IBM <Cost of a Data Breach Report 2025>

ISSUE

Shadow AI & Compromised Credentials

As unauthorized use of generative AI and leaked accounts expand into new attack paths, the risk of intrusions that bypass traditional perimeter-based security is growing.

PwC, 2026 Cybersecurity Outlook: Financial Services

CASE

Cloud Metadata Exposure

In 2024, a major global telecom firm A suffered a leak of customer call and text metadata from a third-party cloud environment, affecting the data of roughly 110 million customers. As a case of third-party cloud access through a leaked account, it revealed the importance of cloud asset visibility and account security.

CASE

Credential Governance Breakdown at Global Data Platform

The attack group UNC5537 used accounts stolen via infostealers to access customer environments at Company S, causing a chain of damage to many customers, including global ticketing company T. The lack of MFA and insufficient account governance were cited as the main causes, showing the need for continuous account verification and privilege control.

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Strategic Data Intelligence
ISSUE

Domain AI Expansion Without Enterprise Context

- as generative AI spreads across enterprise-wide work, a semantic foundation that connects reference information and unstructured data around meaning and relationships is becoming a key condition for AI reliability.

Projected share of enterprise GenAI using domain-specific language models (DSLMs) by 2028 | Gartner, <Top Strategic Technology Trends for 2026>

50%

Gartner, <Top Strategic Technology Trends for 2026>

ISSUE

Enterprise AI Expansion & Governance Challenges

- as AI adoption expands into supply chains, procurement, contracts, and customer service, a framework that manages data quality and operational governance together is determining enterprise-wide AI performance.

Share of large enterprises that have concretely demonstrated enterprise-wide EBIT value and business process innovation through AI investment

5.5%

McKinsey, McKinsey State of AI 2025

CASE

ESG Visibility Failure

A supply chain ESG data management issue at major construction firm M

Global construction and infrastructure firms face difficulties integrating and managing carbon emissions and raw material data across multi-tier supply chains and overseas partners, and the reliability of supply chain data directly impacts ESG disclosure and competitiveness in contract bidding.

CASE

Post-M&A Data Integration Challenge

The challenge of integrating customer data after an M&A at major telecom firm T

After M&A, large telecom firms face difficulties in building a single customer view and conducting cross-service analysis because customer information is scattered across affiliate systems, making data integration a key challenge for improving customer experience and profitability.

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Defined Friction Points

Enterprise Challenges
in the Agentic AI Era

New complex risks in enterprise operations in the age of AI agents

Cyber Security
01

Identity Misuse Beyond Traditional Boundaries

  • -As stolen employee and partner accounts are abused as if they held legitimate privileges, perimeter-based security alone reaches its limits in identifying intrusions
  • -A lack of real-time behavioral analysis delays awareness of breaches, leading to the risk of leaks of core source code and proprietary technology assets
02

Trusted Data Channels Becoming Attack Paths

  • -As the likelihood grows that malicious information enters as legitimate data through external documents, APIs, and collaboration systems, this expands into a new attack surface
  • -If an AI agent executes contaminated data or erroneous commands, there is a risk that it leads to manipulation of internal systems and the performance of unauthorized tasks
03

Visibility Gaps in Autonomous Operations

  • -As automated execution between AI agents and systems increases, traditional log-centric auditing alone reaches its limits in tracing the entire workflow
  • -The speed gap between automated attacks and manual response delays detection, isolation, and recovery, and makes it difficult to assess the scope of impact on services and supply chains
Strategic Data Intelligence
01

Disconnected Enterprise Context Across Business Domains

  • -Systems and reference information separated by business unit and affiliate make it difficult to connect customer, product, supply chain, and contract information into a single flow
  • -Because the semantic systems of structured and unstructured information differ, the reliability of AI results is lower, and frontline decision-making depends on repetitive refinement and verification
02

AI Data Quality & Lineage Breakdown

  • -As generative AI outputs and external data mix into business data, it becomes difficult to trace the source, quality, and change history of information
  • -As data flows and AI execution processes are separated from the governance framework, this creates burdens for operational efficiency, regulatory compliance, and automation management
Industry Approaches

Enterprise Intelligence Framework for Scalable AI & Trusted Operations

An enterprise intelligence framework for scalable AI and trusted operations

Hybrid Asset Exposure Management

Business-Aligned Exposure Management

  • - Identifying group companies, supply chains, and multi-cloud assets and their connection structures, and selecting priority response targets based on business impact
  • - Continuously verifying the accounts and privileges of employees, partners, and AI agents to mitigate the risks of legitimate privilege abuse and disruption to core services

AI Governance for Enterprise Trust

Trusted AI Operations

  • - Managing each business unit's use of generative AI and the movement of critical data to control the risks of Shadow AI and technology asset leaks
  • - Verifying scenarios of prompt injection, privilege misuse, and data poisoning, and reflecting regional regulations and internal policies in the AI operating environment

Intelligence-led Cyber Defense

Threat Intelligence Operations

  • - Correlating APT groups, ransomware, and dark web information with corporate assets to prioritize the threats most likely to have actual impact
  • - Continuously tracking external risk signals including partners and affiliates, and easing the response burden through automated analysis, isolation, and recovery procedures

Unified Context Intelligence

Enterprise Context Foundation

  • - Connecting customer, product, supply chain, design, and contract information through ontologies and knowledge graphs to reduce interpretive gaps across business units and subsidiaries and ensure decision-making consistency
  • - Linking structured and unstructured information from documents, emails, ERP, and collaboration systems to transform tacit knowledge and experience-driven workflows into reusable enterprise assets

Adaptive AI Operations

Decision-centric Automation

  • - Supporting frontline work such as contract review, supply chain analysis, technical support, and risk management through domain-specific AI that reflects the characteristics of each business area
  • - Connecting review, analysis, and reporting tasks that are siloed across departments with AI agents to reduce repetitive work and improve decision-making speed

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Solutions We Provide

Cyber Security

AI Security GovernanceDeep & Dark Web MonitoringAccount Take-over MonitoringCyber Threat IntelligenceAttact Surface ManagementPenetration TestingAI Red TeamingIncident Response

Strategic Data Intelligence

OntologyDomain-specific AIDecision AI