Most SOCs are moving fast – in the wrong direction.
Autonomy raises the stakes: An AI agent handed incomplete, duplicated, or poorly prioritized exposure data reasons its way to the wrong conclusion and then acts on it. Teams end up closing the wrong tickets, chasing the wrong findings, and reporting the wrong wins to leadership.
Brinqa and Torq are changing that.
Join Jay Klauser, SVP of SE & Technical Alliances from Brinqa and Mackenzie Clark, Sr. Partner Engineer from Torq, for a live session on what happens when trusted exposure intelligence meets an agentic AI SOC.
Brinqa's Exposure Management Platform establishes which exposures actually matter through the CyberRisk Graph™: findings deduplicated across every scanner, attributed to a real owner, and prioritized by asset criticality, exploitability, and business impact.
The Torq AI SOC Platform grounds that intelligence in the live state of the environment through the Torq Context Graph, then drives remediation from prioritized finding to verified fix. Two graphs, one decision: the right target, and the confidence to act on it autonomously.
Register to Join
game plan
In this session, you'll see:
game plan
In this session, you'll see:
- Why exposure data quality is the variable that determines whether agentic AI SOC reduces risk or creates noise
- How Brinqa and Torq work together to automate remediation from prioritized finding to verified fix
- What this means for MTTR, analyst hours, and the metrics that matter to your board
Whether you're running a SOC, owning a vulnerability management program, or responsible for exposure reduction at the enterprise level, this session shows what's possible when your AI SOC finally knows what actually matters.
