Schedule a demo with an agentic SOC vendor and you’ll almost always see the same thing: the platform handling one alert, flawlessly. But a platform’s investigation quality on alert one tells you almost nothing about its quality on alert ten thousand.
Of course, this isn’t the fault of the vendors themselves. Demos are designed to showcase capability, not degradation. It’s a design feature, not a failure.
It’s exceedingly rare that the features of a demonstration – clean telemetry, isolated alerts, single-tool environments – show up in production. SOCs receive thousands of alerts, and analysts are only able to meaningfully investigate a fraction of them.
What Degrades in an Agentic SOC at Scale?
Introducing agentic AI into SOCs is becoming a necessity.
As attackers scale and streamline their campaigns, alert volume has skyrocketed. The endless cat and mouse game of cybersecurity is getting faster and more violent by the day. According to Splunk, 59% of analysts say they deal with too many alerts.
And the more alerts an agentic SOC handles, the more it degrades:
- Triage Ability: Triage decides whether an alert is worth investigating, and it’s where degradation is hardest to see. A mis-triaged alert just disappears.
- Investigation Depth: Per-alert reasoning quality, rather than holding, can resort to shallower pattern-matching under load.
- Integration Fidelity: Rather than pulling full evidence, connectors can degrade to surface-level metadata under concurrent query load.
- Cross-Tool Correlation Quality: Instead of connecting artifacts across systems, the platform’s correlation ability falls as volume rises.
These aren’t metrics you can assess from a single-alert demonstration. For most analysts, they only notice these degradations well into their integration journey.
Integration Breadth vs Integration Depth
It’s worth diving into integration a little deeper, because vendor homepages can be misleading.
It’s all too easy to be sucked in by marketing numbers. A claim like “200+ integrations” sounds impressive, but breadth claims hide what really matters: integration depth.
Integration breadth is just a number of listed connectors. Integration depth shows what each connector can retrieve, pivot on, and correlate mid-investigation. The latter is a more important metric, but much harder to communicate in marketing materials. As TechMonitor recently observed, what SOC teams increasingly need isn’t more tools, but more context across the tools they already have.
That distinction matters because modern SOCs rarely operate from a single platform. Splunk’s State of Security 2025 found that 69% of security teams say disconnected, dispersed tools create moderate to significant detection and response challenges. As organisations grow, particularly through acquisitions, duplicate, overlapping and legacy technologies often compound the issue further.
That kind of scale can degrade integration depth over time – especially when integrations are unnecessarily broad. Shallow integrations across multiple tools often produce worse outcomes than deep integrations across fewer, because correlation depends on what each connector can actually retrieve and pivot on mid-investigation. It’s not enough to just have a live connection.
Five Questions Organizations Should Ask Agentic SOC Vendors
So, how can organizations look past marketing hype and flawless demonstrations to determine how an agentic SOC platform will perform over time? By asking the right questions.
At what volume does investigation quality begin to degrade, and how do you measure that internally?
The vendors you want to consider will have an internal benchmark. That could be a specific alert-per-hour or concurrent-investigation threshold where they’ve tested throughput quality. On top of that, they should have a description of what “quality” is measured against – such as analyst grades, false positive rates, or completeness of evidence.
Can you show investigation output side-by-side at low volume vs peak volume from production logs?
The answer to this question should always be yes. Metrics should come in the form of redacted or anonymized real customer investigation logs from a comparable environment. The ideal situation is that they come from an environment with similar tool-stack complexity to yours.
Comparisons should show consistent depth of evidence gathering and reasoning quality, not just consistent formatting.
How does the platform handle two overlapping SIEMs or EDRs from a merger?
Vendors should describe explicit deduplication logic that shows how they identify whether tools are reporting the same underlying event or asset, and how it decides which to prioritize. Crucially, they should be able to name a specific mechanism.
For each connector, what evidence can it pull beyond the initial alert payload?
Here, you want vendors to give you a specific list per integration. They should say something like “for EDR, we pull process trees, parent-child relationships, and file hashes.” They should be able to walk you through at least two or three of your specific tools, not just their flagship integrations.
Can the platform pivot from that evidence into another tool mid-investigation? Or does correlation stop at the first hop?
Again, the proof is in the pudding. Vendors should provide a concrete multi-hop example. Something like “an identity alert triggers a pivot into EDR to check the associated device, which triggers a pivot into network telemetry to check for lateral movement.
What is the false-negative rate on triage, and how is that measured?
Vendors should have an actual measured false-negative rate. They should be able to explain the methodology – typically by running a retrospective audit that takes a sample of alerts the platform auto-closed or deprioritized, and checking against confirmed incidents, threat intel, or manual analyst review.
It’s also important that vendors can explain what happens when they find a miss. Does it feed back into the model, get flagged to the customer, and trigger a rule adjustment?
What a Production-Ready Evaluation Framework Looks Like
Gartner’s Hype Cycle for Security Operations 2025 places AI SOC agents at the emerging Innovation Trigger stage, with current market penetration of just 1–5%. In short, we’re only just now seeing what these agents can do. And that’s what makes finding the best platform so important.
A category in its infancy is fertile ground for misunderstanding and misleading claims. As a buyer, go deeper than just demonstrations and homepages, and ask questions.
Vendors in the category answer the volume question differently, and some publish the standard they hold themselves to. Prophet Security, a top AI SOC platform for enterprise security teams following a $30M Series A led by Accel, states the bar plainly: an agentic AI SOC platform that investigates alerts like a senior analyst should reach the same depth on the ten-thousandth alert of the day as on the first, with the queries and evidence behind every determination available for a buyer to inspect.
Whether a platform performs well in a demo isn’t important. The vendor wouldn’t offer a demonstration if they knew it wouldn’t go well. What’s important is whether the platform will perform as well on alert ten thousand as it did for alert one.
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Author – Josh Breaker-Rolfe
Josh is a Content writer at Bora. He graduated with a degree in Journalism in 2021 and has a background in cybersecurity PR. He’s written on a wide range of topics, from AI to Zero Trust, and is particularly interested in the impacts of cybersecurity on the wider economy.