Your SOC Doesn’t Have a Data Problem. It Has a Coordination Problem.

Security teams have spent years chasing the same fix for stalled risk reduction: buy more tools, add more detection rules, hire more analysts to handle the resulting flood of alerts. But the real issue lies not in gaps in coverage, but in barriers integrating the tools and processes they already have. Most SOCs were built to detect, respond, hunt, and validate as four separate jobs, while security teams are now realizing that these processes need to be tied together in a continuous cycle if we want to build a unified threat exposure data layer that actually holds up against machine speed vulnerability discovery and AI-enabled attacks.

TL;DR:

• The SOC’s problem isn’t lack of data or tools, it’s coordination between tools – still run as disconnected disciplines optimized on their own metrics.
• Agentic AI now closes the gap between “data exists” and “decision made”. XTM One‘s data abstraction layer unifies context from every tool into one queryable model of exposure.
• The real unlock is the loop, not any single workflow. Threat intelligence sharpens validation, validation sharpens prioritization, prioritization sharpens detection – and a system built on that continuous cycle is what actually shifts a SOC from reactive to proactive.

The Problem: Why “More Coverage” Hasn’t Worked

For years, the SOC playbook has been “add more.” More log sources. More detection rules. More tools bolted onto the stack. More headcount to keep up with the alert volume all of that generates.

And yet, for most security teams, risk reduction has plateaued. Not because people aren’t working hard enough but because the SOC was never designed to actually coordinate the capabilities it has.

According to our latest State of Threat Management (SoTM) survey, 47% security professionals report barriers integrating existing tools and processes when trying to improve threat exposure management.

That’s the real problem hiding underneath most “SOC maturity” conversations: it’s not a coverage problem. It’s a coordination problem.

The Silent Cost of Disconnected Security Operations

Most SOCs today run detection, incident response, threat intelligence, and control validation as four separate disciplines. Each optimized locally, each measured on its own metrics, each largely unaware of what the others know.

When every alert is treated as equally important regardless of whether the underlying asset is exposed, exploitable, or even business-critical, SOCs end up scaling headcount and tooling just to keep pace with noise.

The average analyst spends about 42% of their working week on dead-end investigations.

This fragmentation shows up everywhere:

• Detection without context gets expensive fast
• Incident response defaults to urgency instead of impact
• Control validation happens in a vacuum

None of this is a knowledge problem. Security teams know exposure and threat context matter. What’s missing is a mechanism that actually gets that context to the people making decisions, at the moment they’re making them.

Building an Exposure Foundation That Actually Holds Up

Your SOC’s maturity is not in number of tools and data, but its in your response time and ability to take informed decisions. It requires a shared foundation like a cockpit for the security analyst – one place to manage every tool, see the full picture, and act on it, instead of jumping from console to console just to piece together what’s actually happening.

AI-enabled workflows and agentic AI is making this a reality now. Software can now talk to agents, and agents can talk to each other, through emerging standards like Agent-to-Agent (A2A) communication, letting tools coordinate directly instead of waiting for a human to relay context between them. Human-in-the-loop and proper guardrails need to be in place, of course. This could then tremendously improve informed decision making. However, building this foundation isn’t a one-time project, it has to be continuously assembled and kept current, aligning with frameworks like Continuous Threat Exposure Management (CTEM) framework.

According to Gartner, “By 2029, more than 50% of SOC performance gains will come from improvements in exposure data quality, exposure-context integration and workflow alignment rather than from incremental increases in detection volume or tooling complexity.”

Long before ‘exposure management’ became a category analysts wrote reports about, Filigran’s founding bet was simple: to close the loop between threat context → exploitability → validated risk → reduced exposure. Everything we’ve built since: OpenCTI for threat management, OpenAEV for exposure validation and XTM One for agentic AI orchestration and workflows – is that same thread, extended further into the SOC than it’s ever reached before.

Give every SOC function a shared, living understanding of exposure and exploitability – to focus on threats and exposures that matter, reduce false positives and improve decision confidence & outcome quality.

You can’t operationalize exposure data if it’s trapped in silos and this is where an open integrations marketplace stops being a nice-to-have and becomes the prerequisite for everything else to work. Every new integration, your threat intelligence management system, your identity and asset management tools, cloud posture tools, SIEMs, ticketing systems, observability tools – adds another piece of context into a shared, living workflow instead of another isolated report nobody has time to read.

Turning Exposure Data Into Action, Not Just Awareness

Having the right data is only half the equation. The bigger shift is making sure that data actually reaches the point of decision – automatically, in real time, without someone manually stitching it together under pressure.

XTM One’s agentic AI and data abstraction layer makes it actually possible. XTM One’s integrations marketplace closes the physical distance between different sources abstracting away the complexity of where data lives so it can be pulled together into one coherent, shared model of exposure, regardless of which tool, team, or system originally owned it, making it part of the same continuous, queryable picture.

Agentic AI is what closes the second distance: from data available to decision made. Instead of an analyst manually querying five different tools to build context around a single alert, an agent does that correlation continuously, in the background, and surfaces the synthesized answer exactly at the moment it’s needed – inside the alert, inside the incident, inside the hunt. The agent isn’t replacing the analyst’s judgement; it’s removing the delay between “the information exists” and “the person making the call actually has it.”

Demo video: Turning your humble MS Teams session into a war room

This combination – a unified data layer plus agents that can reason across it in real time is what makes threat-informed decisions fast enough to matter. A prioritization call that once took a cross-team meeting and a spreadsheet now happens in the seconds between an alert firing and an analyst opening the case. A response decision that once relied on someone remembering which systems were business-critical now comes pre-loaded with that context, sourced live rather than from a wiki page last updated eight months ago.

This is the leap agentic AI actually enables: not just faster automation of existing steps, but the ability to access and process information anywhere it lives and turn it into a threat-informed decision anywhere it’s needed – without a human being the bottleneck that stitches it all together.

Closing the Loop Is the Whole Point

The real unlock isn’t any single one of these workflows – it’s the loop between them. Threat Intelligence highlights attack paths that need to be tested. Validation results sharpen prioritization. Prioritization sharpens detection. Detection outcomes inform the next round of hunting and testing. Every cycle makes the next one more accurate.

That’s the structural difference between a SOC that’s reactive and one that’s proactive: not fewer alerts, not more tools – a system where every function is working off the same shared, current understanding of risk, and where that understanding gets sharper every time it’s used.

Why We Built It This Way

We didn’t connect intelligence, validation, and orchestration into a single XTM platform because a market category eventually got a name for it. We built this way to bring threat-informed defense to the forefront, one where exposure isn’t a report that lands on a leader’s desk once a quarter, but a closed loop that runs through every decision a security team makes, all day, every day.

Adding more tools and broader detection coverage was never going to be the answer. Coordinated, contextualized decision-making is. That’s what we are building with XTM One, its agentic workflows, and its integrations marketplace to deliver, turning the exposure data organizations already have into the actions that actually reduce cyber risk and ultimately business risk.