DTEX today introduced its expanded AI Risk Management product, extending its platform to secure enterprise use of generative AI tools and autonomous AI agents. As GenAI applications, copilots, and AI agents increasingly operate with access to enterprise data, systems, and workflows, most security solutions still lack the ability to determine human or AI agent intent. DTEX closes that gap with AI Risk Management: a comprehensive suite of AI-native capabilities that apply behavioral intelligence to detect and deter both human and AI-driven risk with the speed and precision of AI.
By combining AI risk management with autonomous investigation and response, DTEX enables organizations to accelerate AI adoption with the visibility, control, and operational confidence required to safely scale AI-driven productivity and innovation across the enterprise.
Monitor and Protect AI Activity
As AI agents begin operating autonomously across enterprise systems, organizations face a new category of risk. Unlike traditional software, AI agents can interpret instructions, access sensitive data, interact with external systems, and make decisions with limited human oversight. Securing these environments requires more than activity monitoring. It requires understanding what the agent was instructed to do, how behavior evolves over time, and whether actions align with expected intent.
DTEX delivers comprehensive visibility into how AI is used across the enterprise and applies deep behavioral context to identify emerging risk before it becomes a breach.
With AI Risk Management organizations can:
- Discover sanctioned and unsanctioned AI usage across users, endpoints, and workflows, including browser, IDE, application, and embedded AI activity.
- Identify shadow AI and embedded copilots in real time, dynamically building sanctioned tool inventories and automatically classifying the risk of unknown or unmanaged AI tools.
- Monitor prompts, responses, and data movement at a granular level, including uploads, downloads, and AI-generated content, to detect leakage of source code, intellectual property, and sensitive enterprise data.
- Classify prompts and interactions to support auditing, compliance, and threat investigations, enabling security teams to understand not just what was asked, but why, through behavioral context and intent analysis.
- Analyze AI activity to infer both human and AI agent intent, distinguishing normal experimentation from risky or malicious behavior by correlating prompts, historical patterns, behavioral baselines, and agent actions over time.
- Differentiate human versus AI-driven actions and deliver deep visibility into “Computer Use” AI (CUI), including what an agent was instructed to do, how it executed tasks, and the detailed lineage of actions performed across enterprise systems.
- Detect and prevent autonomous agent-driven data exfiltration using behavioral monitoring, prompt lineage, and AI risk models that proactively identify high-risk agentic behavior and the intersection between human and AI risk.
In one early deployment, DTEX identified an autonomous AI agent exposing sensitive enterprise data despite operating within its intended workflow and permissions. By correlating prompt lineage, behavioral patterns, and contextual activity over time, DTEX surfaced the risk before it resulted in a security incident.
Act on Risk with Autonomous Security Agents
To make AI Risk Management operational, DTEX is also introducing autonomous security agents that apply behavioral context and risk modeling to automate investigation and threat analysis. This enables organizations to differentiate human vs AI-driven activity, track behavioral patterns over time, and understand how AI systems interact with data and identities.
Triage Guardian Agent
Built on more than 20 years of DTEX i³ behavioral expertise, Triage Guardian applies a multi-agent approach to deliver consistent, defensible triage outcomes at scale. Unlike traditional alert-driven workflows that evaluate isolated events, Triage Guardian continuously analyzes behavioral context before, during, and after an incident, allowing agents to effectively rewind and fast-forward investigative timelines to understand how risk evolved over time. It automates investigation workflows, gathers contextual evidence, and applies structured human oversight through independent reviewer agents that validate findings, minimize bias, and ensure conclusions remain evidence-backed. By combining behavioral intelligence with analyst-grade decision logic, Triage Guardian dramatically reduces false positives while minimizing missed risks that conventional triage approaches often fail to detect.
Threat Hunter Agent
Threat Hunter enables proactive threat discovery through agentic workflows, continuously assessing the evolving risk landscape, generating detailed threat analysis, and identifying previously unknown threats before they surface in an incident. Analysts can initiate complex threat hunts using natural language, allowing Threat Hunter to determine how to execute the investigation, correlate findings, and surface relevant risk autonomously. Built on more than 25 years of DTEX i³ threat hunting expertise, including collaborative research with MITRE and FVEY defense partners, Threat Hunter applies proven analyst tradecraft and investigative context to every hunt at machine speed.
Availability
DTEX AI Risk Management is currently available in private preview. Organizations can request access, with broader availability expected next quarter.
Organizations can learn more and request access at www.dtex.ai/ai-risk.
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This entry was posted on June 9, 2026 at 12:00 pm and is filed under Commentary with tags DTEX. You can follow any responses to this entry through the RSS 2.0 feed.
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DTEX Introduces AI Risk Management
DTEX today introduced its expanded AI Risk Management product, extending its platform to secure enterprise use of generative AI tools and autonomous AI agents. As GenAI applications, copilots, and AI agents increasingly operate with access to enterprise data, systems, and workflows, most security solutions still lack the ability to determine human or AI agent intent. DTEX closes that gap with AI Risk Management: a comprehensive suite of AI-native capabilities that apply behavioral intelligence to detect and deter both human and AI-driven risk with the speed and precision of AI.
By combining AI risk management with autonomous investigation and response, DTEX enables organizations to accelerate AI adoption with the visibility, control, and operational confidence required to safely scale AI-driven productivity and innovation across the enterprise.
Monitor and Protect AI Activity
As AI agents begin operating autonomously across enterprise systems, organizations face a new category of risk. Unlike traditional software, AI agents can interpret instructions, access sensitive data, interact with external systems, and make decisions with limited human oversight. Securing these environments requires more than activity monitoring. It requires understanding what the agent was instructed to do, how behavior evolves over time, and whether actions align with expected intent.
DTEX delivers comprehensive visibility into how AI is used across the enterprise and applies deep behavioral context to identify emerging risk before it becomes a breach.
With AI Risk Management organizations can:
In one early deployment, DTEX identified an autonomous AI agent exposing sensitive enterprise data despite operating within its intended workflow and permissions. By correlating prompt lineage, behavioral patterns, and contextual activity over time, DTEX surfaced the risk before it resulted in a security incident.
Act on Risk with Autonomous Security Agents
To make AI Risk Management operational, DTEX is also introducing autonomous security agents that apply behavioral context and risk modeling to automate investigation and threat analysis. This enables organizations to differentiate human vs AI-driven activity, track behavioral patterns over time, and understand how AI systems interact with data and identities.
Triage Guardian Agent
Built on more than 20 years of DTEX i³ behavioral expertise, Triage Guardian applies a multi-agent approach to deliver consistent, defensible triage outcomes at scale. Unlike traditional alert-driven workflows that evaluate isolated events, Triage Guardian continuously analyzes behavioral context before, during, and after an incident, allowing agents to effectively rewind and fast-forward investigative timelines to understand how risk evolved over time. It automates investigation workflows, gathers contextual evidence, and applies structured human oversight through independent reviewer agents that validate findings, minimize bias, and ensure conclusions remain evidence-backed. By combining behavioral intelligence with analyst-grade decision logic, Triage Guardian dramatically reduces false positives while minimizing missed risks that conventional triage approaches often fail to detect.
Threat Hunter Agent
Threat Hunter enables proactive threat discovery through agentic workflows, continuously assessing the evolving risk landscape, generating detailed threat analysis, and identifying previously unknown threats before they surface in an incident. Analysts can initiate complex threat hunts using natural language, allowing Threat Hunter to determine how to execute the investigation, correlate findings, and surface relevant risk autonomously. Built on more than 25 years of DTEX i³ threat hunting expertise, including collaborative research with MITRE and FVEY defense partners, Threat Hunter applies proven analyst tradecraft and investigative context to every hunt at machine speed.
Availability
DTEX AI Risk Management is currently available in private preview. Organizations can request access, with broader availability expected next quarter.
Organizations can learn more and request access at www.dtex.ai/ai-risk.
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This entry was posted on June 9, 2026 at 12:00 pm and is filed under Commentary with tags DTEX. You can follow any responses to this entry through the RSS 2.0 feed. You can leave a response, or trackback from your own site.