At Torq, our commitment to security has always been at the forefront of our mission to empower businesses through our SaaS platform. Today, we’re proud to announce a significant step forward in our security journey: Torq has signed the CISA Secure by Design Pledge. This pledge underscores our dedication to ensuring that our customers can trust our platform to uphold the highest security standards, enabling customers to focus on their goals without concerns about their security posture.

For security teams, resolving a cloud incident takes an average of 10 days — time attackers can exploit to cause further damage. The problem? SOCs often lack the context and cloud security automation they need to respond faster. That’s where the partnership between Torq and Sweet Security changes the game.

Last year was an absolutely amazing year for Torq. The stats are just mind-blowing: 300% revenue growth and 200% employee growth. We also closed our $70M Series C round, bringing our total funding to $192M.

SOC teams often wrestle with clunky, siloed reporting tools that lack real-time, connected capabilities. Analysts end up buried under a mountain of fragmented xdata, forcing teams to spend valuable hours tracking down answers to their most pressing questions, rather than tackling threats head-on. At Torq, we feel SOC reporting should be your power move, not a painful process.

Case management for modern SOCs can be a maze of endless alerts, overwhelming data, and intense pressure. Legacy solutions often exacerbate these issues with rigid workflows, limited automation capabilities, and a lack of real-time adaptability, leaving teams ill-equipped to handle the growing complexity of threats. The volume of cases, manual workflows, and processes leave analysts overwhelmed, exhausted, and struggling to keep pace.

Gal Peretz is Head of AI & Data at Torq. Gal accelerates Torq’s AI and data initiatives, applying his deep learning and natural language processing expertise to advance AI-powered security automation. He also co-hosts the LangTalks podcast, which discusses the latest AI and LLM technologies. Our previous blog post explored how planning with AI systems can set the stage for smooth collaboration between humans and machines. However, a solid plan alone isn’t enough.

With widespread remote work and global access, organizations face mounting challenges in securing user identities against sophisticated threats. One critical identity risk signal is impossible travel, where a user appears to log in from two unrecognized, geographically distant locations within an unrealistic timeframe, indicating the possibility of compromised credentials or session hijacking.

As C-suites and boards are bombarded with headlines about AI revolutionizing cybersecurity, it’s no wonder they’re putting pressure on SOC leaders to adopt AI. The promise of AI in the SOC is rightfully alluring. An AI-native autonomous SOC has the potential to create a world where AI Agents collaborate with each other to take care of repetitive tasks and handle the majority of low-level alerts, freeing your human team up for strategic, proactive work. The hurdle?

Meet Torq Socrates and learn how a Large Language Model (LLM)-powered AI SOC Analyst can revolutionize SecOps. Artificial intelligence (AI) in the SOC has generated significant hype in recent years, and separating the promise from reality can be challenging. However, at Torq, AI is not just a concept — it is a reality that is revolutionizing the SecOps field, specifically in the area of Tier-1 security analysis.

The rise of Non-Human Identities (NHIs) — think APIs, bots, service accounts, and machine identities — has expanded the attack surface in ways we’re only beginning to understand. NHIs now outnumber human identities in enterprise environments, often by a staggering ratio. While they streamline processes, enable scalability, and facilitate automation, these identities also present significant security risks.