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Retail

Connecting Customers, Commerce and Every Retail Touchpoint

Retail intelligence connecting customers and commerce as one

Retail Intelligence
for Resilient Omnichannel Growth

An omnichannel growth architecture powered by retail intelligence

By connecting customers, products, stores, and supply chains in an integrated way, we improve operational efficiency while strengthening both the stability of digital services and the customer experience.

Market Dynamics & Trends

Smarter, Safer Retail
Through Connected Data

Retail Intelligence Powered by Connected Data

Cyber Security
ISSUE

Always-on Retail Operations

Securing 24/7 retail operational continuity

The stable operation of ordering, payment, membership, and inventory systems has become a key factor determining customer experience and revenue, and cyber breaches lead directly to service disruption and eroded trust.

ISSUE

Growing Retail Attack Surfaces

The Hyperconnected Retail Ecosystem and Its Expanding Attack Surface

As omnichannel services, mobile apps, SaaS, and supply chain platforms become interconnected, externally exposed assets and third-party risks are rapidly increasing.

CASE

Online Sales Disruption Impact

An online service disruption at global retailer M

As online ordering, payment, membership, and supply chain systems become primary targets of cyberattacks, securing operational continuity and customer trust is becoming increasingly important.

Online ordering service outage

46 Days

Reuters (2025)

Estimated operating profit loss

$404M

Reuters (2025)

CASE

Retail Ecosystem Outage Risk

An operational outage at global automotive retail platform C

A failure in a core platform spread to sales, settlement, and customer service, revealing operational risks across the entire retail supply chain.

Retail locations affected by the operational disruption

15,000+

Reuters (2024)

1/2

Strategic Data Intelligence
ISSUE

Connected Customer & Commerce Data

Retail operations connecting omnichannel data

The more online, offline, logistics, and membership data are scattered, the harder it becomes to understand customers and inventory in an integrated way. Data-driven operations that connect customers, products, and channels are becoming the core of retail competitiveness.

ISSUE

AI-driven Store Operations

Advancing AI-Powered Store Operations

AI is expanding beyond demand forecasting and inventory management into store operations, staff tasks, and customer service, accelerating data-driven operational optimization.

CASE

AI-enhanced Workforce Productivity

AI-driven store operations innovation at global retailer W and global coffeehouse chain S

Using AI-powered inventory recognition, the risk of stockouts and the time staff spend on warehouse management are being reduced, improving the availability of popular products.

U.S. store staff using the AI work assistance tool

1.5M

Reduction in shift planning time

▼60 Min.

1/2

Defined Friction Points

Retail Challenges in Data-driven & Secure Operations

The challenges of data-driven retail operations

Cyber Security
01

Growing Retail Attack Surfaces

  • -External exposure expands to include customer accounts, payments, e-commerce, SaaS, and supply chain systems
  • -Account takeover and service disruptions directly affect revenue and customer trust
02

Complex Security Operations Across Retail Ecosystems

  • -Security events across cloud, stores, supply chains, and external services are managed in a fragmented way
  • -Rising alerts and limited security staff slow down threat analysis and response
Strategic Data Intelligence
01

Fragmented Retail Intelligence

  • -POS, online store, membership, and inventory data are scattered, making it difficult to grasp customers, products, and inventory in an integrated way
  • -Demand changes and inventory flows cannot be connected in real time, delaying pricing, promotion, and ordering decisions
02

Execution Gap Across Stores & Supply Chains

  • -Operational automation, inventory management, order processing, and store tasks are run largely through repetitive manual work
  • -Omnichannel processes such as cross-channel delivery, in-store pickup, and returns are disconnected, reducing operational efficiency
Industry Approaches

Retail Intelligence Framework for Growth & Protection

Retail operational visibility limited by fragmented data

Digital Commerce Protection

Commerce Threat Management

  • - Correlating CTI, dark web, and leaked credentials to proactively identify threats to brands, customer accounts, and e-commerce services
  • - Using ATO and bot intelligence to detect account takeover, card testing, and malicious automation, strengthening the trustworthiness of online transactions

Unified Security Operations

Business-Centric Exposure Management

  • - Using ASM, the attack paths and exposed assets across e-commerce, SaaS, cloud, and supply chain assets are continuously verified
  • - Based on AI SOC and business impact analysis, detection, analysis, and response are optimized around service impact

Retail Ontology & Knowledge Intelligence

Semantic Commerce Intelligence

  • - Using ontology and knowledge graphs, customer, product, inventory, and channel data are connected to analyze customer behavior and product relationships in an integrated way Through a semantic layer, decision-making and collaboration efficiency are improved across merchandising, marketing, and store operations teams
  • - Integrating the operational context of production, quality, equipment, and procurement teams through a semantic layer, and supporting consistent manufacturing decisions through multi-domain cross-analysis

Agentic Store & Fulfillment

Retail AI Orchestration

  • - AI agents automate store operations, inventory replenishment, price changes, and order and return tasks to improve on-site operational efficiency
  • - Using predictive fulfillment, demand forecasts are linked with supply chain data to optimize inventory allocation and fulfillment operations
Use Cases & Operational Success

A customer data-driven AI analytics case at global retailer L

43 million member records

A generative AI-powered retail trend analysis service

Using ontology, knowledge graphs, and RAG, we correlated the consumption data of 43 million members with external news data to deliver trend analysis and generate customized reports. Through a domain-specific LLM and AI Chat, we provided context-based analysis and Q&A on customer behavior, product sales, and market trends, supporting product development and marketing strategy.

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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