R
CLAVI MINING
Home
Solutions
Case Studies
Resources
SEO
Contact
Seminar
Loading
Case Study 15

Company C: Business Application SIer for Railway and Logistics

AI agent groups autonomously protect business applications for railway and logistics operations.

Achieving both social infrastructure quality and sustainable maintenance capacity

AI AGENT COMMAND

24-hour autonomous security operations

Railway

Logistics

Maintenance

An operations model where vulnerability response is completed without waking engineers

Industry

Contract development and maintenance of business applications for the railway and logistics industries

Implementation target

Security operations department for all provided applications

Implementation period

2-month PoC → 6-month phased rollout

OVERVIEW

24-hour operations supporting social infrastructure

Company C is an SIer that provides business applications supporting social infrastructure, including operation management, reservations, cargo tracking, and maintenance management for railway operators and logistics companies. Because customers’ transport and logistics operations run 24 hours a day, vulnerability response has also required around-the-clock readiness. As manual nighttime response approached its limit, the company applied CLAVI Mining agent technology to build an operations model in which vulnerability response can be completed without waking engineers.

MISSION RISK

Challenges before implementation

24-hour security operations

Insufficient capacity for 24-hour security operations supporting social infrastructure that operates around the clock

1

Company C faced a shortage of capacity for 24-hour security operations supporting social infrastructure that runs around the clock. When critical vulnerabilities were disclosed at night or on holidays, maintenance engineers had to be called in for emergency response, resulting in an average of about 20 emergency callouts per month.

2

In the railway and logistics industries, changes that could lead to business stoppages are unacceptable, so impact assessment before applying vulnerability patches must be extremely careful. Manual assessment had reached its limits, and the dilemma of delayed response versus shallow impact assessment had become constant.

3

Management clearly recognized that operations supporting a 24-hour society require security that operates autonomously 24 hours a day, leading to the decision to shift to autonomous operations using AI agents.

AGENT ARCHITECTURE

Reasons for selection

MULTI AGENT FLOW

Execute

Verify

Supervise

The most important selection criterion was careful autonomous operation that would not increase business stoppage risk. A design that entrusted everything to a single AI could not satisfy the risk tolerance required for social infrastructure. CLAVI Mining’s multi-agent mutual monitoring architecture matched the industry’s risk requirements by minimizing business impact through a three-layer check of execution, verification, and supervision.

The ability to finely design human intervention points was also important for the operational characteristics of the railway and logistics industries. Critical changes during peak periods, such as around first-train hours or logistics busy seasons, could require human review, while other time slots could be completed by AI up to automatic approval candidate status.

The patented hallucination suppression technology became a decisive basis for final management approval as a foundation for structurally reducing the risk of incorrect actions in social infrastructure.

RESULTS

Effects after implementation

【Nighttime and holiday emergency callouts】

Monthly average: 20 → 2

A 90% reduction. Maintenance engineers’ quality of life improved significantly, and their intention to leave also improved greatly.

【Vulnerability response lead time】

3–5 business days → 30 minutes on average

A 98% reduction. For the first time, the company achieved a structure capable of responding to vulnerabilities disclosed late at night.

【Customer evaluation from railway operators and logistics companies】

Nearly perfect score

The careful design that did not increase business stoppage risk was highly evaluated, and medium-term maintenance contract renewals were completed at a nearly perfect level.

【Business continuity】

Core BCP technology

As an SIer supporting social infrastructure, agent operations were positioned as core technology for the business continuity plan (BCP). Operational continuity during disasters and pandemics was greatly strengthened.

COMMENT

Comment from the maintenance manager: “Vulnerability response can be completed without waking people. This is what modern social infrastructure maintenance should look like. AI agents now protect people while also protecting society.”

INSIGHTS

Insights from this case

INSIGHT 1

Company C’s case shows an important message: for SIers supporting social infrastructure, 24-hour autonomous security operations are also a talent strategy. Reducing the burden of nighttime and holiday response improves engineer retention and, as a result, enhances both organizational sustainability and service quality.

INSIGHT 2

AI agent operations should be positioned not only as a cost-reduction measure, but also as an investment with multifaceted management value, including talent retention, organizational sustainability, and BCP readiness.

BCP

Relationship with BCP and social infrastructure responsibility

1

With the introduction of agent operations, Company C also reviewed its BCP for disasters and pandemics. Agents operating autonomously 24 hours a day become a foundation that continues to protect systems even when field teams cannot operate during BCP activation.

2

In fact, during a large-scale disaster in 2024, agent operations functioned as expected. Even when maintenance engineers could not reach the site, autonomous response to urgent vulnerabilities published by JVN was completed. Security operations that do not stop even during disasters are becoming a new quality standard for SIers serving social infrastructure.

3

The existence of this foundation was also highly evaluated in BCP assessments by customers such as railway and logistics operators, becoming a trust base for long-term maintenance contract renewals. The idea of using AI to continue work that would stop with human-only operations during disasters is increasingly becoming central to the industry.

* This article is a dummy case study created as a structural example. Company names and figures are fictional.