Pick a security conference this year and you’ll hear the same pitch from at least eight booths: an “AI SOC analyst” that triages Tier-1 alerts, runs the investigation, and hands your humans a fully written ticket. The pitch isn’t wrong. Some of these products are actually good. But the category has bloated to the point where a CISO running a POC has to decide between platforms that look identical on a feature matrix and behave wildly differently the moment a real alert lands.
This post is the comparison I wish I’d had before the last three POCs I sat in on. It’s vendor-neutral, opinionated, and focused on the question that matters: which of these tools fits your SIEM, your alert volume, and your appetite for letting software make calls without a human in the loop.
What “AI SOC” actually means in 2026
Three different products get sold under the same banner. Mixing them up is how POCs go sideways.
Triage-only platforms read the alert queue and rank what’s worth a human’s time. They might enrich an alert with asset context, deduplicate, or guess severity, but they hand the investigation back to you. Useful, cheap to run, low risk. Also limited — your analysts still do most of the work.
Investigation agents go further. They pull logs from your SIEM, query endpoint data, hit threat intel APIs, follow the trail across systems, and produce a written investigation with evidence. The human decides what to do about it. This is where the bulk of the market sits today, and it’s where the ROI math actually works for most SOCs.
Autonomous-resolution platforms close tickets without you. They mark benign alerts as resolved, push back on the EDR, isolate a host, lock an account. Vendors love the word “autonomous.” Buyers should treat it like “self-driving” — there’s a long spectrum between “lane-keep assist” and “no steering wheel,” and you really want to know which one you’re buying.
The other axis: SIEM-coupled vs alert-source-agnostic. Charlotte AI is married to CrowdStrike. Purple AI lives inside SentinelOne. Prophet, Dropzone, and Radiant pull from Splunk, Sentinel, Chronicle, Panther, CrowdStrike, SentinelOne, and whatever else you wire in. If your stack is one vendor end-to-end, the bundled agents are tempting. If it’s not, an independent platform is usually the cleaner integration story.
Prophet Security
Prophet has been the loudest growth story in the category over the last year, and the reason isn’t marketing — it’s that their multi-agent investigation actually produces reports a Tier-2 analyst doesn’t roll their eyes at. The system runs several specialized agents (triage, enrichment, hypothesis-testing, summary) in parallel and they argue with each other before producing a finding.
Where Prophet wins: SIEM-agnostic, strong on Splunk and Sentinel, mature handling of multi-source alerts, the investigation timeline is auditable rather than a black box. They lean into the “investigation grade” framing — every claim ties to evidence the analyst can click through.
Where it’s less of a fit: if you want fully autonomous closure of benign alerts, Prophet’s default posture is conservative. It surfaces a recommendation; the human acts on it. You can stretch that with SOAR integrations, but if your goal is “fewer humans on the queue,” Dropzone is the more direct pitch.
Dropzone AI
Dropzone made the “autonomous Tier-1 analyst” pitch its whole identity. The product investigates and closes — or escalates — without a human in the loop on benign alerts, which is exactly the value prop overstretched SOCs want to hear. The evidence package it produces is among the cleanest in the category. Reports read like a junior analyst wrote them: hypothesis, what they checked, what they ruled out, what they recommend.
Worth knowing: “autonomous” here still depends on the policies you set. Out of the box Dropzone won’t take destructive action — it’ll close obvious false positives and escalate everything else. That’s the right default. If you’ve heard the pitch as “replace a junior analyst” and assumed that means no oversight, calibrate expectations during POC.
Where Dropzone is the strongest fit: mid-market and lower-enterprise SOCs with 10–50 analysts where the alert queue is the bottleneck and you’d genuinely benefit from auto-closing the 60–80% of alerts that turn out to be nothing. Where it gets harder: highly regulated shops where audit teams want a human signature on every closure regardless of confidence — you can configure for that, but you’re paying for autonomy you can’t use.
Torq HyperSOC
Torq came up as a SOAR vendor — workflow automation, no-code orchestration — and HyperSOC is the AI investigation layer they bolted on top. That heritage is the feature and the limitation in one.
The feature: if your SOC already runs on heavy automation and you have engineers who think in playbooks, Torq slots in. The agent kicks off investigations that hand back to your existing Torq workflows for response, and the round-trip feels natural. The integration breadth (hundreds of connectors) is best-in-class.
The limitation: the AI investigation depth doesn’t feel as native as Prophet’s or Dropzone’s. It’s competent. It’s also not the thing Torq has been building longest. If you don’t already have a SOAR-shaped hole in your stack, you might be paying for orchestration you won’t use.
Honest take: pick Torq if your decision is really “I need SOAR and I want AI investigation included.” Don’t pick it if your decision is “I need the best AI investigation and I’ll figure out automation later.”
Anvilogic
Anvilogic comes from the detection-engineering side of the house. The pitch is for SOCs that already invest in writing and tuning their own content — Sigma rules, custom analytics, ML detections — and want an AI layer that respects that work rather than replacing it.
This is the right choice for a specific buyer: mature SOCs (40+ analysts, dedicated detection engineering function) who have spent years tuning their stack and don’t want a vendor making opinionated judgments about their alerts. Anvilogic’s “bring your own detection” model is unusual in the category and it’s a strength if you fit the profile.
If you don’t have a detection-engineering team, Anvilogic is overkill. The product asks more of you than Prophet or Dropzone do. You get more control in return, but only if there’s somebody on staff to wield it.
Radiant Security
Radiant frames the product as analyst augmentation rather than analyst replacement, and the tone of the platform reflects that. The agent investigates, presents findings, and stops short of acting. MSSPs love this model because they can present Radiant’s output as their own analyst work product to clients, with a human always in the chain.
Where Radiant is a clean fit: MSSPs, lean in-house SOCs that need to look bigger than they are, and any team where compliance or culture demands a human signature on closures. The platform is genuinely good at making three analysts feel like ten without crossing the autonomy line.
Where it gets cramped: if you want autonomous closure at volume, Radiant isn’t trying to be that product. That’s a positioning choice, not a flaw. Just know what you’re buying.
Charlotte AI (CrowdStrike) and Purple AI (SentinelOne)
The EDR-bundled agents are the easy answer for stacks that are already all-in on one vendor, and the hard answer for everyone else.
Charlotte AI is tightly integrated with Falcon’s telemetry. If your SOC’s center of gravity is CrowdStrike — endpoint, identity, cloud, NG-SIEM — Charlotte gives you investigation depth on Falcon data that no third party can match, because no third party has the same access. The same logic applies to Purple AI inside the Singularity platform: deeply integrated with SentinelOne’s data, weak on data that doesn’t live there.
The catch: as soon as your alert source is outside the EDR vendor’s universe — a Snowflake audit log, a Cloudflare anomaly, a custom Sigma rule firing in your own SIEM — the bundled agents go from “best in class” to “uncomfortable.” You either accept the gap, build glue, or run an independent platform alongside.
My read: if you’re 80%+ on one EDR vendor and your SIEM is theirs too, the bundled agent is probably the right call and you don’t need to read the rest of this post. If you’re a mixed shop, the independent platforms are a cleaner story.
Worth mentioning
A few platforms are notable without being in everyone’s POC shortlist yet.
Crogl is the autonomy-forward upstart that newer SOCs talk about most often — small team, sharp product, real autonomous closure. Worth a POC slot if you’re explicitly hunting for less-mainstream options.
Conifers has carved out a niche with multi-tenant MSSP buyers who want Radiant’s posture with stronger tenancy controls.
Intezer comes from the malware-analysis side and the investigation depth on suspicious binaries is unique. Less interesting as a general Tier-1 analyst, very interesting as a specialist alongside one.
ReliaQuest GreyMatter is the MDR-with-AI play. It’s an outsourced service first and a platform second, which is a different buying decision — you’re buying SOC capacity, not software.
Pricing — and what to actually negotiate
The category hasn’t standardized on a model and that’s good news for you in procurement. The three patterns:
Per-alert volume. Sounds clean, ages badly. As your detections improve and you tune down noise, your bill should go down. Vendors don’t always price that way in practice. Push for a stepped model where the per-alert rate drops as volume drops.
Per-analyst-equivalent FTE. A platform priced “as if it were N analysts.” Honest framing for autonomous platforms (Dropzone), creative bookkeeping for everyone else. Negotiable.
Flat platform fee with usage caps. Best deal if you can predict alert volume; worst if you can’t. Insist on overage rates, not “contact us” caps.
What to negotiate hardest: data egress out of your SIEM. Some of these platforms run investigations by ingesting log data into their own backend. Your Splunk or Sentinel bill will move. Get the vendor to either pull in-place via search APIs or commit to a token/query budget. This is the single biggest hidden cost in AI SOC.
A six-week POC scorecard that actually measures something
The vendor-supplied POC templates are useless. Steal this one instead.
- Week 1–2: shadow mode. The platform investigates every alert your humans investigate, no actions. Compare findings.
- Week 3–4: precision and recall on benign closures. Of the alerts the agent calls benign, how many were actually benign? Of the malicious ones it caught, how many did your team also catch? Anything under 95% precision on benign closure is a no.
- Week 5: time-to-close. Median minutes from alert fired to ticket closed, AI vs human-only. The graph matters more than the headline number — outliers tell you where the agent breaks.
- Week 6: analyst override rate. How often did your humans disagree with the agent’s call? Anything over 15% means you’re not saving the time the vendor projected.
Metrics that don’t matter and will be pushed on you: total alerts processed, “hours saved” (vendor math), CSAT from your analysts (politeness bias).
Choosing by stack
If you take one thing from this post: the right answer depends more on your stack and team than on the vendors’ relative quality.
- Splunk-heavy, mixed EDR: Prophet or Dropzone. Both are mature on Splunk.
- Microsoft Sentinel + Defender: Prophet, Dropzone, or wait for Security Copilot to grow up — it’s not there yet for full Tier-1 work.
- Chronicle + Mandiant: Prophet is the safe call. Google’s own offerings are improving but still patchy on autonomous closure.
- Panther-native, modern stack: Dropzone integrates cleanly; Prophet a close second.
- All-in CrowdStrike: Charlotte AI, with a Prophet or Dropzone overlay only if you have meaningful non-Falcon sources.
- All-in SentinelOne: Purple AI, same caveat.
- MSSP or “make us look bigger”: Radiant, or Conifers if multi-tenancy is the bottleneck.
- Mature detection-engineering team that already owns its content: Anvilogic.
One thing to try this week
Pull last quarter’s Tier-1 alert volume and split it into three buckets: alerts your humans closed as benign in under five minutes, alerts that took meaningful investigation, and alerts that escalated. If bucket one is more than half your volume — and it usually is — you have a Dropzone-shaped problem. If bucket two dominates, you have a Prophet-shaped problem. If your team can’t even tell you the split, you have a detection-engineering problem first and an AI SOC problem second.
Run the math before you sit through another demo.