What good is a security platform that floods your team with 4,000 alerts a week and can’t tell a real attack from a misconfigured printer? That question comes up in every Claroty, Dragos and Nozomi Networks evaluation, and it is the one vendors work hardest to dodge. All three sell visibility into operational technology (OT) and industrial networks. All three publish glossy reports, quote analyst grids, and promise “actionable intelligence.” None of them will hand you a spreadsheet showing how often their alerts are wrong. (Wi fi airtime fairness or off actually works real networks) (CISA: Industrial Control Systems)
So the buyer is left to build the comparison themselves. This guide shows how to do that with a framework you can defend to a CFO, a plant manager and an auditor at the same time.
Why output quality is the only comparison that matters in 2027
Operational technology is the hardware and software that detects or causes a change through direct monitoring or control of physical devices, processes and events, as defined in Gartner’s operational technology glossary entry. A pump that stops is not an inconvenience; it is a safety event, a regulatory event and possibly a headline.
That raises the stakes on every alert. In IT security, a false positive costs an analyst twenty minutes. In OT, a false positive can trigger an unnecessary plant shutdown, and a false negative can mean a compromised safety instrumented system nobody noticed. The detection and triage burden is serious enough that NIST’s Computer Security Incident Handling Guide treats false positives and negatives as a core part of the detection and analysis lifecycle rather than a nuisance to be tolerated.
Vendors rarely compete on that axis because it is hard to market. They compete on coverage claims, integrations and threat research. Those matter, but they are inputs. Output quality is the output: what the tool actually tells you, how often it is right, and whether a human can act on it before the shift ends. (Claude vs chatgpt writing draft quality compared across)
What “output quality” actually means for OT security tools
There is no single published standard for scoring OT platform output, and anyone claiming otherwise is selling something. In practice, evaluation teams converge on four measurable axes. Treat this as a working framework, not a certified benchmark.
| Axis | What it measures | How to test it |
|---|---|---|
| Asset discovery accuracy | Completeness and correctness of the inventory | Compare against a physical walkdown and network captures |
| Alert precision | Ratio of true positives to total alerts | Run a two-week shadow mode with known test events |
| Contextual enrichment | Protocol-aware detail: who, what, where, why | Check whether alerts name the asset, zone and protocol |
| Export fidelity | How cleanly data lands in SIEM, CMDB or ticketing | Map fields to your schema and count manual fixes |
Notice that three of the four axes are testable before you sign anything. That is the point. A proof of concept that only demonstrates a dashboard is a sales demo with better lighting.
Asset discovery: the foundation everything else rests on
If the inventory is wrong, every downstream alert inherits the error. Ask each vendor to identify a specific, deliberately messy subnet: legacy PLCs with no credentials, a few unmanaged switches, a medical device or two, and at least one asset that changed IP address mid-week. Then walk the floor with a clipboard and compare.
Practical tip: plant engineers usually know the truth better than any scanner. Bring one to the walkdown. They will spot the phantom asset the tool invented and the real controller it missed.
Alert precision: the number vendors won’t volunteer
Ask for the false-positive rate in writing. Most will deflect to “tuned environments” or “customer-specific.” That deflection is your answer. A better approach is to run a controlled test: inject known-benign traffic (a firmware update, a scheduled backup, a maintenance laptop plugging in) and count how many alerts it generates.
The vendors approach this problem differently. Dragos built its model around its platform plus Neighborhood Keeper, a collective-defense network that pools anonymized threat data across customers, and it publishes an annual Year in Review threat report that has run since at least 2017. Nozomi Networks leans on passive, agentless monitoring paired with threat-intelligence feeds. Claroty positions itself as the broadest in scope, spanning industrial OT, enterprise IoT and connected medical devices.
None of those descriptions tells you the false-positive rate. Only your own test does.
Contextual enrichment: does the alert explain itself?
An alert that says “suspicious traffic on VLAN 40” is noise. An alert that says “unauthorized Modbus write to dosing controller PLC-7 from engineering laptop 10.4.2.19, outside the maintenance window” is a decision.
Score each vendor on whether alerts name the asset, its physical location, its network zone and the protocol involved. This is where the underlying data model matters more than the interface. The Purdue Model, codified in the ISA/IEC 62443 series of standards, is the conventional way OT networks are segmented and described, and a platform that maps cleanly to those zones will produce alerts your team can route. One that invents its own taxonomy creates translation work forever.
Export fidelity: the unglamorous dealbreaker
Ask how many fields survive the trip into your SIEM. Then ask how many need manual mapping. Teams routinely discover in month three that their shiny new platform exports asset names but drops zone information, forcing analysts back to the vendor console for every investigation.
Test this in the proof of concept. Export a week of alerts to your actual ticketing system and count the clicks.
How the three vendors differ in what they produce
The honest summary: Claroty, Dragos and Nozomi are all credible platforms with different center of gravity, and no public, peer-reviewed head-to-head benchmark of their output quality exists. Any comparison chart you find is likely vendor-sourced or analyst opinion. Treat it accordingly.
| Dimension | Claroty | Dragos | Nozomi Networks |
|---|---|---|---|
| Historical center of gravity | Broadest scope: OT, IoT, IoMT | OT threat intelligence and services | Passive monitoring plus threat intel |
| Signature output | Cross-domain asset visibility | Threat reports and collective defense data | Agentless network monitoring feeds |
| Best fit when | You need one view across plant and building | You want deep adversary context | You want low-touch deployment |
Two caveats. First, vendor packaging and product naming change yearly, so verify current offerings rather than trusting any article, including this one. Second, report titles and editions shift constantly; confirm the exact edition before citing one in an internal business case.
There is one more trap worth naming. CVSS severity is not OT risk. A CVSS 9.8 in a system that cannot be reached from any network is not the same emergency as a CVSS 6.5 on an internet-facing device. CVSS scores severity in the abstract, not exploitability in your environment, and the FIRST CVSS specification and version history explains exactly what the score does and does not capture. Teams that rank OT alerts purely by CVSS number will chase the wrong fires.
A practical evaluation method you can run in four weeks
Here is a sequence that has survived contact with real plant schedules.
- Week one: define the truth. Pick one production line or building. Walk it with a plant engineer and build a manual asset list. This is your benchmark.
- Week one: set the test events. Schedule a firmware update, a backup window and a maintenance laptop connection. Tell the vendor nothing about the timing.
- Weeks two and three: run shadow mode. Deploy passively. No blocking, no automated response. Let all three platforms run against identical traffic if your procurement allows parallel trials.
- Week three: score against public benchmarks. Check whether each tool flags assets exposed to vulnerabilities on CISA’s Known Exploited Vulnerabilities catalog, which lists flaws with confirmed in-the-wild exploitation. This is a free, neutral yardstick.
- Week four: export and triage. Push alerts into your real SIEM and ticketing system. Have two analysts triage blind and time the exercise.
- Week four: write the scorecard. Use the four axes above, weighted by your environment. A water utility and a semiconductor fab will weight them differently, and that is fine.
One more useful check: MITRE Engenuity’s ATT&CK Evaluations publish results from vendor products run against emulated adversary behavior. Coverage of OT network monitoring vendors is partial and varies by year, so check which evaluation rounds included ICS scenarios before drawing conclusions, but where your vendor appears, the results are worth reading.
If your evaluation team is also comparing AI research assistants for the report writing that follows, this comparison of Perplexity and ChatGPT research citation quality is a reasonable starting point. And if the same project touches plant networking, the guide to how Wi-Fi airtime fairness on or off actually works on real networks covers the wireless side that OT teams often forget.
Common mistakes that wreck an OT platform comparison
Testing on a clean lab network. Vendors love labs. Labs have no legacy chaos. Insist on production traffic, passively monitored.
Letting the vendor tune during the trial. Tuning is legitimate, but it must be documented and counted as labor. If a vendor spends forty engineering hours suppressing noise, that is forty hours your team will spend later.
Ignoring the analyst experience. A platform with 95 percent precision and an unusable interface loses to one with 85 percent precision and a clean workflow. Watch a real analyst use it for an hour.
Skipping the integration audit. Ask for the field mapping document before signing, not after.
Treating alert volume as a feature. More alerts is not more coverage. It is more work.
Conclusion
The Claroty vs Dragos vs Nozomi question has no universal winner, and anyone who tells you otherwise is guessing or selling. What does have a winner is the evaluation method. Build a ground-truth asset list, inject known events, score precision and enrichment, export to your real tools, and write it all down.
Do that, and the platform choice becomes an evidence-based decision rather than a beauty contest between three dashboards. Your plant engineer, your SOC analysts and your auditor will all thank you. The vendors might not, but they were never the point.
FAQ
Is there an independent benchmark comparing Claroty, Dragos and Nozomi output quality?
No public, peer-reviewed head-to-head benchmark of these three platforms exists as far as can be determined. Published comparisons tend to be vendor-sourced or analyst opinion. MITRE Engenuity’s ATT&CK Evaluations offer the closest thing to neutral testing, but OT network monitoring coverage is partial and varies by year. The most reliable benchmark is your own controlled proof of concept.
How long should an OT security platform proof of concept run?
Four weeks is a workable minimum. Two weeks of passive shadow mode generates enough data to score alert precision, and the surrounding weeks cover ground-truth asset walks, export testing and analyst triage timing. Anything shorter tends to capture only the cleanest traffic and flatters every vendor equally.
What false-positive rate should we expect from OT monitoring tools?
There is no published industry figure that holds across environments, which is exactly why vendors avoid the question. Expect meaningful noise in the first weeks regardless of vendor, and evaluate the tuning effort required rather than the raw initial count. Ask each vendor to document how many engineering hours tuning consumed during the trial.
Does CVSS score tell us which OT vulnerabilities to fix first?
Not on its own. CVSS measures severity in the abstract, not exploitability in your specific environment. A high score on an unreachable device can matter less than a moderate score on an internet-facing system. Combine CVSS with exposure data, such as whether the vulnerability appears on CISA’s Known Exploited Vulnerabilities catalog, and with your own network segmentation.
Do we need all three platforms, or can one cover OT, IoT and medical devices?
One platform can cover all three domains if its scope genuinely spans them, which is Claroty’s stated positioning. The real question is whether the depth in each domain meets your needs. A single console is convenient, but a broad tool that produces vague alerts across every domain is worse than a focused tool that produces precise ones where it counts.
What is the single most useful test during an OT platform trial?
The blind triage test. Have two analysts review the same week of alerts without vendor guidance, time how long each takes, and compare their conclusions. It measures precision, enrichment and usability in one exercise, and it predicts what daily operations will actually feel like after the contract is signed.
