Brinqa, a leader in unified exposure management, has introduced two innovative AI-driven agents designed to address some of the most persistent and costly challenges in enterprise cybersecurity: ambiguous asset ownership and duplicate exposure signals. These new capabilities the AI Attribution Agent and AI Deduplication Agent enhance decision confidence and accelerate risk reduction at scale.
Modern enterprises generate vast volumes of security data, yet ambiguous ownership details and overlapping findings across scanners and tools slow remediation, inflate risk metrics, and complicate executive oversight. Brinqa’s latest platform release tackles these bottlenecks head-on, providing clarity, accountability, and streamlined remediation workflows.
Intelligent Agents Built for Real-World Exposure Challenges
Unlike traditional rule-based systems, Brinqa’s AI agents operate continuously on the platform’s trusted data foundation, reducing manual effort while preserving human oversight and approval.
The AI Attribution Agent identifies and infers missing asset attributes such as owner, business unit, or environment designation — using machine learning models trained on existing enterprise data. Every inference includes transparent reasoning, traceability, and confidence scoring, enabling security teams to validate and approve suggested assignments.
The AI Deduplication Agent uses its intelligence to combine multiple, overlapping exposure signals from various security tools into single, richer records. Essentially, the agent correlates sets of findings that, at their core, indicate the same issue even though the taxonomy, severity, or naming conventions may differ thereby providing a more straightforward, accurate view of the company’s exposure. It also gets rid of phantom findings and makes sure that the remediation tickets are in line with the actual risk.
“As attack surfaces expand and security tool sprawl grows, leaders find themselves with more data and less confidence. That’s a trust problem. This release addresses it head-on with AI-native agents built into a platform architected for AI from the ground up. Deduplication, ownership attribution, and SmartFlow automations all transparent, all explainable, all designed to turn exposure management into a trusted and disciplined, continuous system for reducing real risk.” Dan Pagel, CEO of Brinqa.
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Integrated Architecture for Continuous Exposure Risk Management
Brinqa’s AI agents are not add-on modules; they are embedded at the core of a unified platform architecture that continuously learns, adapts, and improves exposure decisioning and action. This living system comprises three synchronized layers:
• Data Layer: Normalizes and unifies exposure, asset, and threat data into a trusted foundation.
• AI Layer: Transforms raw data into actionable intelligence while keeping humans in control.
• Orchestration Layer: Automates remediation actions and enables guided, cross-team workflows.
The combined architecture enables enterprises to continuously manage risk, ensuring that AI recommendations are explainable, traceable, and linked to measurable outcomes.
Scalable Data Infrastructure with Historical Intelligence
At the heart of Brinqa’s platform is its CyberRisk Graph™, a proprietary data model that maps relationships across exposure data, assets, and threat intelligence to provide a dynamic and accurate view of risk. Unlike static models, this graph evolves with the enterprise environment, contextualizing and cleansing data to support confident decision-making.
Brinqa also integrates BrinqaDL, an intelligent data lake that preserves historical exposure and remediation records. This long-term context supports auditability, trend analysis, forensics, and AI-driven decisions, helping security teams understand how risk evolves over time and the impact of remediation efforts.
Orchestration for Faster, Measurable Remediation
The platform’s orchestration features offer a visual representation of data, help with easy, to, understand steps, and enable no, code automation through SmartFlows which is a drag, and, drop workflow builder that can send alerts, make tickets, and direct troubles by the established business logic. In conjunction with ready, made dashboards that emphasize the most pressing discoveries, these functionalities assist teams to focus their efforts and respond to risk in a more efficient manner.
