A Critical Milestone: Yandex Cloud Automates One-Third of SOC Routine Tasks with Multi-Agent AI

Strengthening Digital Resilience

Yandex Cloud has deployed a multi‑agent system built on Yandex AI Studio, automating about 39% of routine security‑operations tasks. The system now handles incident monitoring, correlation, internal database search, and identification of similar past cases.

The implementation reduced the time spent processing false or low‑quality alerts by 86%, dramatically increasing SOC efficiency. Yevgeny Sidorov, Yandex Cloud’s Chief Information Security Officer, emphasizes that modern SOC teams must combine cybersecurity expertise with the ability to use advanced AI tools effectively.

For Russia’s IT sector, this is a significant precedent: a major infrastructure provider is successfully automating security workflows. The gains strengthen the resilience of digital systems—a critical factor for business, government, and national infrastructure. For security specialists, AI offloads repetitive work, enabling them to focus on higher‑complexity threats and strategic challenges.

Scaling and Export Potential

If successful at scale, this approach could be adopted not only within Yandex Cloud but across Russian IT and telecom companies, cloud providers, and government organizations—raising national cybersecurity standards.

“In two years, we moved from piloting AI in the SOC to full‑scale industrial use. RAG technologies played a crucial role, giving models access to up‑to‑date documents and incident databases. The multi‑agent approach improved accuracy: tasks were distributed across specialized agents capable of working with the deep context of large enterprises.”

Yevgeny Sidorov,

Chief Information Security Officer at Yandex Cloud

It also marks a step toward an ‘autonomous SOC,’ where AI agents manage operational workloads while human analysts focus on threat hunting, complex incident response, and strategic security planning.

Russia’s increasingly competitive AI‑security technologies may also find demand internationally, especially among countries seeking alternatives to Western platforms. Domestically, this shift will drive demand for professionals skilled in both AI and information security as machine‑learning‑based cyber‑defense solutions grow.

Proactive Security

In 2025, AI has become both a defensive tool and a weapon leveraged by attackers. Emerging threats include deepfakes, adaptive malware, and GPT‑powered phishing.

Security teams use AI for vulnerability discovery, attack prediction, phishing detection, and malware analysis. Building AI‑powered defense is essential: real‑time attack recognition, automatic blocking, continuous staff training, and rapid information sharing are now foundational requirements.

The 2025 study “AI‑Powered SOC Operations” shows that combining machine learning with predictive analytics enables SOCs to detect, analyze, and respond to attacks in real time, reducing analyst workload. Automation filters false positives and accelerates investigations. AI does not replace analysts—it amplifies them, provided that training data quality is high.

From 2023 to 2025, SOCs worldwide shifted toward the ‘AI + human’ model: anomaly detection via ML, explainable AI for decision transparency, and LLMs for simplifying log analysis.

According to Vedomosti, Russian companies—especially in finance—are increasingly using ML and neural networks for proactive cybersecurity, preventing incidents before they occur. Experts predict that by 2026 proactive cyber defense will become a dominant global and domestic trend.

A New Stage

Yandex Cloud’s deployed solution reflects the broader shift of 2023–2025: AI is moving from experimental to production‑grade technology in cybersecurity. Russia is likely to see rapid expansion of similar projects from enterprises, integrators, security vendors, and SaaS providers over the next one to three years.

For society and business, this means more reliable, rapid, and automated protection of data and critical services.