Artificial intelligence (AI) continues to reshape the cybersecurity landscape, offering new levels of automation and efficiency. In a significant stride for next-generation threat detection tools, Secure.com has launched its AI-powered assistant, Digital Security Teammate (DST), following a successful $4.5 million seed funding round. The DST technology exemplifies a growing trend in “agentic security”—a term used to describe AI agents designed to autonomously handle various aspects of security operations, from routine incident triage to more complex escalations.
DST Is Built to Perform Continuous, Autonomous Incident Response
The Digital Security Teammate is not positioned as a typical chatbot or security information and event management (SIEM) dashboard add-on. Instead, DST is designed as a long-running autonomous agent that can integrate deeply into a security operations center (SOC) and perform continuous tasks without human prompting. Acting like a virtual security analyst, DST can detect incidents, conduct automated investigations, and escalate threats based on environment-specific impact.
This agentic approach is setting a new bar for incident response automation. Rather than querying systems passively or waiting for user input, DST proactively initiates investigations as suspicious behaviors unfold. Secure.com claims DST continuously refines its interpretations of threat data by maintaining environmental context over long timeframes—allowing it to understand what normal and abnormal behavior looks like in a specific network or organization.
DST Works in Tandem With Security Teams, Not as a Replacement
Secure.com positions DST not as a human replacement but as an augmentation layer that alleviates the overwhelmed SOC teams facing a deluge of alerts. By handling routine false positives and emerging low-risk incidents, DST allows human analysts to focus on more sophisticated threats and proactive threat hunting. This aligns with a broader shift in cybersecurity operations toward intelligent workload distribution using AI cybersecurity tools.
The AI system focuses on three primary actions:
- Investigation : Upon identifying anomalous behavior, DST autonomously runs queries and analyzes system logs to determine the scope and nature of an incident.
- Triage : Based on contextual understanding, it assigns severity scores and filters out less-relevant data, offering analysts curated insights.
- Escalation : For confirmed or high-impact threats, DST notifies analysts with comprehensive incident summaries and recommended actions—reducing time to resolution and improving decision-making efficiency.
Seed Funding Supports Broader Rollout of Agentic Security Framework
The $4.5 million seed funding round was led by several cybersecurity-focused investors and will allow Secure.com to expand both its engineering team and customer footprint. According to the company, agentic security represents a paradigm shift, enabling continuous security operations without compromising accuracy or generating alert fatigue. The funding will also support integrations with SIEMs, extended detection and response (XDR) platforms, and identity systems, such as Active Directory.
Agentic security, unlike traditional automated scripts or workflow engines, emphasizes autonomous agents acting on intent, state, and context. These agents are capable of initiating actions themselves—significantly more powerful than waiting for human-triggered playbooks. As organizational networks grow more complex and distributed, the need for persistent and adaptive tools increases. DST and similar tools could play a critical role in delivering these capabilities.
Challenges and Considerations in Adopting AI Agents in Security Environments
Despite its promise, agentic security also introduces new challenges. Decision granularity, explainability of AI behavior, and security against AI subversion are major concerns. Misclassification of benign activity as malicious—or vice versa—could result in operational friction or vulnerabilities. Secure.com emphasizes that DST operates with a high degree of transparency, offering visibility into its reasoning models and training data sources. However, widespread adoption of such agentic systems will require trust, robust audit trails, and consistent validation.
Security teams must also assess how agent-driven tools align with their existing workflows. Integrating AI incident response tools into tightly regulated environments or government operations may necessitate compliance-specific adaptations.
A Glance Into the Future of AI in Cyber Defense
Secure.com’s strategic bet on DST reflects the increasing pressure on enterprises to reduce mean time to detect (MTTD) and mean time to respond (MTTR) using AI-powered tools. As threats evolve and adversaries become more sophisticated, traditional manual review processes are proving insufficient. The launch of DST suggests that fully autonomous agents may soon become foundational elements of the modern SOC, working 24/7 to identify, understand, and respond to threats without requiring constant human input.
As agentic security matures, DST’s capabilities could expand to include predictive threat modeling, scriptless response automation, and integration with AI-driven threat intelligence platforms. For now, its successful launch and funding round represent a promising step toward a more scalable and proactive security posture.
