We are proud to share that Eventus has been featured by the Japan External Trade Organization (JETRO) in its latest Investing in Japan newsroom article: Eventus Hong Kong Limited Establishes Japanese Subsidiary in Tokyo to Provide AIoMT Platform.

Published on August 24, 2026, the feature recognizes Eventus’s expansion from Hong Kong into Japan and introduces our work in AIoMT—Artificial Intelligence of Medical Things. It also highlights how our Tokyo subsidiary, Eventus K.K., is helping bring practical healthcare and cybersecurity solutions to the Japanese market.

Security teams are not short on alerts. They are short on time, context, and attention.

A 2025 survey of 2,058 security leaders found that 59% receive too many alerts, while 52% described their SOCs as overworked. Security Magazine’s summary of the research also found that many teams lose investigation time because their security data is difficult to manage and disconnected across tools.

The human cost is just as clear. In the 2025 ISC2 Cybersecurity Workforce Study, 48% of respondents said they felt exhausted from trying to keep up with new threats and technologies, while 47% felt overwhelmed by their workload. ISC2’s study surveyed more than 16,000 cybersecurity professionals and decision-makers.

This is alert fatigue: the point where every notification starts to look the same, every investigation feels urgent, and analysts have to spend more energy deciding what to ignore than determining what matters.

It is not a company-specific problem. It is an operational problem affecting security teams everywhere.

At 9:02 on Monday morning, a public-facing firewall starts recording a port scan.

By 9:05, the SIEM has generated 5,000 alerts. The IT lead opens the dashboard, sees a wall of red, and asks the question every small security team eventually asks:

“Can’t we just put AI on top of the SIEM and have it tell us what matters?”

It is a reasonable question. The right direction is, in fact, AI on top of SIEM. Your existing SIEM already collects events, applies detection rules, and stores the evidence. An AI layer can translate that output into priorities, explanations, and next actions.

That is the idea behind SIEM+, an AI security overlay for teams that want better triage and clearer security posture without replacing the SIEM they already operate.

A generic chatbot, a one-off LLM script, or a loosely connected AI copilot may produce an impressive answer to one alert. Security operations require something more durable: a system that remembers context, groups related evidence, respects data boundaries, tracks posture over time, and produces outputs people can act on and defend later.

Every audit season, the same scene plays out. A security team exports a mountain of raw logs, a spreadsheet of alert counts, and a screenshot of a dashboard covered in red and yellow blocks. They hand it to the auditor and hope for the best.

The auditor doesn't want any of that. They want one question answered clearly: "Can you prove this control is working, and show me the evidence?" If the answer takes twenty minutes of dashboard-squinting to extract, you've already failed the real test — not of your security posture, but of your ability to communicate it.

This is the problem we built the SIEM+ (siem.plus) Auditor View to solve. Not "more visibility." Comprehensible visibility — audit-ready by default, not audit-ready after a week of manual report building.

We’re pleased to share a new Eventus article on Qiita: “The Full Story of SEKHMET, a Software-Defined Gateway That Eliminates Dedicated Hardware.”

Published in Japanese, the article introduces our vision for making IoT deployments lighter and more accessible. Instead of requiring a dedicated gateway for every project, SEKHMET uses software on existing smartphones and tablets to connect sensors, process data at the edge, and link operational information with cloud services.