Everyone is selling an AI SOC. Almost nobody defines it.
The vocabulary is still forming, which makes it easy to sell and hard to buy. This page separates the five things the phrase is currently used to mean, says which of them exist today, and is specific about where we sit on that ladder rather than implying the top of it.
An AI SOC is a security operations center where machine learning performs work that previously required an analyst: correlating signals across sources, enriching them, discarding noise and ranking what remains. It does not mean the analysts are gone.
Five distinct things get called an AI SOC: traditional, automated, AI-assisted, agentic and autonomous. The first three are widely deployed. Agentic is emerging and real. Autonomous, meaning detection through response with no human in the loop, is not something anyone is delivering today.
Vijilan is AI-assisted and moving toward agentic. Praxis AI™ is the SOC platform: it correlates, triages and orchestrates response across every connected source, and a Vijilan analyst owns the decision at every layer, which is detection, escalation and response.
The same two words, five different products.
Naming the rungs is most of the value, because a provider two rungs below where you assumed will still answer yes when you ask whether they use AI.
- 01
Traditional SOC
Humans read alerts from a console. Scale is bounded by headcount, which means coverage is bounded by budget, which is why out-of-hours gaps exist at all.
- 02
Automated SOC
Rules, playbooks and SOAR handle defined sequences. Fast and reliable for the cases somebody anticipated; silent on the cases nobody did, which are the ones that matter.
- 03
AI-assisted SOC
Models do the first pass: correlation, enrichment, deduplication, ranking. The analyst opens a case rather than a queue. This is where most credible providers actually are, including us, and it is a genuine step change in throughput.
- 04
Agentic SOC
Multiple specialized agents pursue an investigation, gather their own context and propose a course of action, rather than executing one predefined path. Emerging, real, and not the same thing as autonomous.
- 05
Autonomous SOC
Detection through response with no human in the loop. Nobody is selling this today whatever the marketing says, and the reason is not that the models are weak. It is that irreversible action on a production estate is an accountability question before it is a technical one.
Where Vijilan actually sits, stated rather than implied.
AI-assisted, moving toward agentic. Praxis AI™ is the SOC platform Vijilan built. It correlates telemetry across every connected source, ranks the queue, and orchestrates response across the systems it can reach by API, so an analyst opens the case that matters rather than the one that arrived first.
A Vijilan analyst owns the decision at every layer: detection, escalation and response. That is a boundary rather than a limitation we are working to remove. Machine speed where speed wins, human judgment where judgment is what the situation needs.
Praxis runs alongside CrowdStrike’s own platform intelligence inside Falcon Next-Gen SIEM rather than replacing it, and extends the same operating standard to third-party sources Falcon does not own.
The parts worth their own page.
Including the uncomfortable ones.
What is an AI SOC?
A security operations center in which machine learning does work that used to require an analyst: correlating signals across sources, enriching them with context, discarding noise and ranking what remains. The term does not imply the humans are gone, and in every credible implementation today they are not.
Is an autonomous SOC real yet?
Not in the sense the phrase implies, and it is worth being exact rather than diplomatic about it. Detection, triage, correlation and investigation are all largely able to be automated today and the gains are large. Response is where it stops, because isolating a production host or disabling an executive’s account at 3am is a decision somebody has to own. Anyone claiming full autonomy is describing a roadmap.
So where does Vijilan actually sit?
AI-assisted, moving toward agentic. Praxis AI™ is the SOC platform: it correlates, triages and orchestrates response across every connected source so an analyst opens the case that matters rather than the one that arrived first. A Vijilan analyst owns the decision at every layer, which is detection, escalation and response. We would rather say that plainly than claim a category we have not reached.
What is the difference between an AI SOC and an agentic SOC?
An AI SOC uses models as tools inside a process a human still drives. An agentic SOC delegates goals rather than tasks: agents decide what to investigate next, gather the context they need and propose an action. The distinction is about who chooses the next step, and it is the reason the two terms are not interchangeable even though they are marketed as if they were.
Does AI reduce false positives?
It reduces how many reach a human, which is not quite the same claim and is the one worth making. The volume still exists; automation absorbs the obvious portion of it so analyst attention lands on the ambiguous remainder. That is where the throughput gain comes from, and it is real.
What happens if the AI is wrong?
On the first pass it costs time, because a human reviews what was escalated and, periodically, samples what was not. That sampling is the part to ask any provider about, because a system that only checks its own escalations cannot discover what it wrongly dismissed. On response, the answer is that automation does not take irreversible action unsupervised, which is the whole reason for the boundary.
Is this the same as Charlotte AI or Falcon IQ?
No. Those are CrowdStrike’s, and Vijilan operates on the CrowdStrike platform rather than building it. Praxis AI™ is the SOC operations layer Vijilan built: analyst workflow, triage queue and response orchestration spanning third-party telemetry as well as Falcon data. It runs alongside CrowdStrike’s own platform intelligence rather than replacing it.
Ask us where the
automation stops.
It is the question that separates providers in this category, and most answers to it are evasive. Ours is a boundary we can describe precisely, which is easier to evaluate than a promise.