ExtraHop brings the Agentic SOC to FDC Summit 2026 as cyber defense moves to machine speed
Security Operations Centers were built around humans reading alerts, investigating suspicious activity and deciding what to do next.
ExtraHop believes that model is reaching its limit.
The cybersecurity company is participating in FDC Summit 2026 with a strategy built around the rise of the Agentic SOC, where AI agents can investigate threats, correlate evidence and support response at machine speed rather than waiting for analysts to manually work through every alert.
ExtraHop specializes in Network Detection and Response, or NDR, using real-time network data to detect suspicious behavior and give security teams visibility into activity across devices, users, applications and cloud environments.
Its flagship RevealX platform uses network telemetry as a source of context, allowing security teams to understand what happened before, during and after a suspicious event rather than relying on an isolated endpoint or log alert.
ExtraHop wants to rebuild the SOC around AI
The strongest technology story ExtraHop could bring to FDC Summit emerged in July, when the company launched the Agentic SOC Alliance alongside a group of cybersecurity companies including CrowdStrike, Torq, ReversingLabs, Command Zero and Dropzone AI.
The initiative is designed to define a shared operating model for security operations powered by autonomous AI agents.
ExtraHop proposes an architecture based around three major layers: Context, Harness and Model.
The model provides reasoning, the harness connects agents with security tools and workflows, while context gives those agents the evidence they need to understand what is actually happening inside an enterprise environment.
The company’s argument is straightforward: giving an AI agent access to powerful security tools is not enough if the information used to make decisions is incomplete or unreliable.
Network data becomes the AI agent’s evidence
This is where ExtraHop sees its biggest role in the Agentic SOC.
An AI security agent investigating an alert needs to know more than whether malware was detected on one computer.
It may need to understand which systems that device communicated with, whether credentials were used elsewhere, whether data moved between servers and whether the attacker attempted lateral movement through the network.
ExtraHop uses deep protocol analysis to correlate activity across devices, identities, applications and infrastructure, turning network traffic into structured information that AI agents can use during an investigation.
In February, the company expanded its capabilities specifically to provide what it describes as the deep context required for autonomous security operations.
The aim is to allow agents to triage, enrich and respond to threats while reducing the amount of manual investigation required from SOC analysts.
AI creates another security problem
ExtraHop is not only using AI to defend enterprise networks.
It is also trying to protect the AI systems companies are rapidly deploying.
In March 2026, the company introduced new capabilities designed to continuously discover AI infrastructure and monitor how it interacts with corporate systems.
That includes identifying large language models running across cloud and on-premises environments, detecting unauthorized AI tools and tracking infrastructure such as Model Context Protocol servers and APIs.
The issue is becoming increasingly important as AI agents gain access to databases, applications and sensitive information.
Traditional security products may see an approved AI agent communicating with an approved application and consider the traffic legitimate.
But if the agent has been manipulated or compromised, the behavior occurring inside that trusted relationship may still be dangerous.
ExtraHop’s approach is to use the network as a continuous source of evidence about what those systems are actually doing.
From Shadow AI to a complete AI asset inventory
One of the practical problems enterprises are beginning to face is simply identifying how much AI is already operating inside the organization.
Business teams can adopt AI services without informing security departments, developers can connect applications to external models, while new AI agents can appear inside cloud environments quickly.
ExtraHop is therefore building what amounts to an AI asset inventory.
The company says its technology can discover approved and unauthorized AI assets, map their communication patterns and establish a baseline for normal behavior.
That capability could become particularly relevant for large enterprises attending FDC Summit.
Before an organization can govern AI usage, it first needs to know where AI is being used.
The rise of Shadow AI means that this is becoming more difficult than it sounds.
Ransomware shows why speed matters
The push toward machine-speed security is not driven by AI alone.
Attackers are already moving through enterprise environments quickly enough to expose the limitations of traditional investigation processes.
ExtraHop’s 2026 Global Threat Landscape research found that nearly half of organizations affected by ransomware experienced data theft before the attack was detected.
The findings point to a persistent gap between initial compromise and the moment security teams understand the full extent of an incident.
That is exactly the gap the Agentic SOC is intended to reduce.
Instead of an analyst opening multiple tools and manually reconstructing an attack, AI agents could use network, identity and endpoint context to begin the investigation automatically.
Humans would remain involved in high-risk decisions, but much of the initial evidence gathering and triage could happen without waiting for a person to start the process.
Investigation time is already falling
ExtraHop is also using performance data to support its case for network-driven investigations.
A study published by the company in April found that organizations using its NDR platform accelerated cyber threat investigations by 63%, highlighting the impact of providing analysts with richer network evidence from the beginning of an investigation.
That becomes even more significant when AI agents enter the SOC.
Faster investigation is useful when humans are performing the work.
For autonomous systems, access to reliable context becomes essential because an incorrect automated decision could potentially disrupt legitimate business systems as quickly as it stops an attacker.
ExtraHop therefore argues that speed alone is not enough.
Machine-speed security also needs decisions that can be explained and defended.
A different proposition at FDC Summit 2026
ExtraHop brings a different cybersecurity discussion to FDC Summit than companies focused primarily on endpoint protection, application security or threat intelligence.
Its focus sits deeper inside the enterprise network.
Every cyberattack eventually creates activity between systems, whether an attacker is stealing credentials, moving laterally, accessing a database or extracting information.
ExtraHop is betting that this network activity can provide the context AI needs to understand an attack rather than simply react to another alert.
For banks, government organizations, telecom operators and other large enterprises attending FDC Summit, that could become increasingly relevant as both attackers and defenders adopt artificial intelligence.
The future SOC may still have human analysts at its center.
But if ExtraHop’s vision proves correct, those analysts will increasingly work alongside autonomous agents capable of carrying out much of the investigation before a human ever touches the case.
At that point, the competitive advantage in cybersecurity may no longer belong to the team that can respond fastest.
It may belong to the team whose AI understands what is happening first.