operational resilience

  • Commvault Unveils Cloud AI Workload Undo Feature

    Commvault’s AI Protect offers an “undo” button for autonomous AI agents in cloud environments, addressing governance gaps. This solution discovers, monitors, and rolls back AI actions across AWS, Azure, and GCP, mitigating risks from rapid AI deployments. It provides granular control to revert environments to a known good state, even differentiating AI changes from legitimate human actions, enhancing operational resilience and security in the age of advanced AI.

    2026年4月15日
  • Robust AI Governance: Safeguarding Enterprise Margins

    To protect margins and foster innovation, businesses must prioritize robust AI governance, moving from opaque proprietary systems to open infrastructure. As AI becomes foundational, closed development becomes untenable due to complexity, security risks, and integration challenges. Open-source AI enhances operational resilience through broad scrutiny and collaborative improvement. Embracing transparency and open foundations is crucial for enterprise AI’s future, enabling adaptability, innovation, and public legitimacy.

    2026年4月10日
  • Asylon and Thrive Logic Partner for Physical AI in Enterprise Perimeter Security

    Thrive Logic and Asylon partner to introduce “Physical AI” for network edge security. This integration combines Asylon’s robotic patrols with Thrive Logic’s AI agent analytics for proactive, autonomous incident detection and response. The goal is to minimize response times, enhance operational resilience, and provide security leaders with reliable, auditable coverage in exterior security zones. This human-AI collaboration shifts security from reactive to strategic oversight.

    2026年4月7日
  • .How Background AI Boosts Operational Resilience and Shows Clear ROI

    summary.Enterprises gain the greatest AI ROI not from customer‑facing chatbots but from silent back‑office systems that flag irregularities, automate risk reviews, and ensure compliance. These “invisible” engines continuously analyze data—PDFs, invoices, logs—to detect anomalies, prevent costly audits, and uncover fraud or supply‑chain inefficiencies, saving millions. Success depends on educated professionals who integrate AI with domain knowledge, maintain transparency, and adapt models over time. By pairing expert supervision with precise, background AI, firms achieve operational resilience, reduced risk, and measurable cost savings.

    2026年1月18日