Tells you something broke
Thresholds, alerts, and a per-device bill.
How we compare
Monitoring watches. Log analytics stores. Event intelligence explains.
Three categories, three different jobs. This page compares them by category and never by company name.
Stores what happened
Indexed logs, a search bar, and an ingest-based bill.
Tells you why, and what next
Correlation across vendors, root cause with its evidence, a next step.
- Root cause is built in
- Flat pricing, not ingest-based
- Your data never leaves
- An assistant for your NOC
The three categories
What each one is actually for.
Each one answers a different question. The eight-hour triage lives in the gap between them.
What a monitoring stack does
It watches. It polls devices, checks metrics against thresholds, and raises an alert when one is crossed.
- Strong at detection and alerting.
- Usually priced per device.
- Root cause is left to the engineer.
What a log analytics platform does
It stores and searches. A search bar answers the question you already knew how to ask.
- Strong at storage, search and retention.
- Priced on ingest, by the gigabyte.
- Root cause is an add-on rather than the default.
Where event intelligence sits
It explains. Events, configs, tickets and topology get correlated across vendors and come back as a probable root cause with a next step.
- Strong at correlation, root cause and remediation guidance.
- Flat pricing, not tied to data volume.
- Runs alongside the monitoring you already have.
Uncorrelated
- Core router
- Aggregation A
- Edge firewall
- Load balancer
- Access A
- Access B
- Aggregation B
- Core router
- Access A
- Edge firewall
Correlated
Core routerupstream
- Aggregation A
- Aggregation B
- Edge firewall
- Load balancer
- Access A
- Access B
Same infrastructure, wiped from uncorrelated to correlated.
Side by side
Five rows that decide it.
Find the column that describes your current spend and read across.
| Capability | PulsarOps AI | Legacy log analytics | Monitoring suites | Cloud-only AIOps |
|---|---|---|---|---|
| Pricing model | Flat | Ingest-based | Per-device | Per-GB |
| Root cause | Built-in | Add-on | No | Partial |
| On-prem | Yes | Partial | Yes | No |
| Data sovereignty | Yes | Partial | Partial | No |
| AI assistant | Yes | No | No | Partial |
Scroll the table sideways on a narrow screen.
Row by row
Why each row is in the table.
A tick is a summary. Open a row for the reasoning.
Ingest-based and per-GB pricing tie the bill to how much data your infrastructure produces, and networks only produce more. Teams react by dropping sources and shortening retention, which removes the evidence root cause analysis needs.
PulsarOps AI is flat, which works out 2-4x more cost-efficient over three years.
Three-year estimate: five-person NetOps team, ~125 incidents/yr, triage cut from 8 hours to 1.
Monitoring suites raise the alert and stop there by design. Log analytics sells root cause as an add-on, and cloud-only AIOps flags the unusual without explaining it.
In PulsarOps AI it is built in. Pattern-based correlation and ML-based classification run across interfaces and devices, and the finding arrives with its evidence and a recommended action.
Monitoring suites are usually happy on-premise, log analytics is partial, and cloud-only AIOps is cloud-only by design.
PulsarOps AI deploys inside your perimeter, in-country, or in your own cloud account with your keys and your controls.
Sovereignty is a different question from on-premise. A platform can install on your hardware and still route analysis through a region you did not choose.
PulsarOps AI deploys in-country for government and regulated operators. The security page walks through what that means.
A search box with autocomplete is not an assistant. The test is whether an engineer can ask in plain language and get back a summary, the evidence, the raw logs, and a next step.
The agentic RAG assistant queries event logs, configurations and topology, then answers with proof.
Why PulsarOps AI
Built to troubleshoot, not just to monitor.
Four decisions that separate this from a log search bar with a chat box bolted on the side.
01
Root cause is built in
Not a paid add-on. Every answer carries the evidence behind it, so the engineer closing the ticket can show their working.
02
Flat pricing, not ingest-based
Your bill tracks your team, not your data volume. 2-4x more cost-efficient over three years.
Three-year estimate: five-person NetOps team, ~125 incidents/yr, triage cut from 8 hours to 1.
03
Your data never leaves
On-prem, private cloud, or a sovereign data center. In a regulated evaluation this is the question that comes first.
04
An assistant for your NOC
It augments your engineers with correlation and next steps. Senior troubleshooting knowledge becomes something a second-line engineer can reach on shift.
Correlation filter
2 incidents
Noise is caught. The incidents fall through.
The cost case
What the difference is worth over three years.
The saving is triage your engineers stop doing by hand.
Download the CTO ROI brief
Event
Same device
Other device
Same window
New window
New window
Same window
one incident
One path lights. The rest go dim.
- Incident recovery
- 50-75%
- faster incident recovery
- Return on investment
- 228%
- annualized ROI
- Payback
- 3.7 mo
- payback period
- Cost efficiency
- 2-4x
- more cost-efficient over three years
Three-year estimate: five-person NetOps team, ~125 incidents/yr, triage cut from 8 hours to 1.
Not a rip and replace
You are not being asked to switch anything off.
PulsarOps AI runs alongside the monitoring you already have. What changes is the hour after the alert.
- Keep your existing detection and alerting.
- Keep your ticketing, and feed it in as a source.
- Add correlation across interfaces, devices and vendors.
- Add a root cause with the evidence and the raw logs attached.
- Add recommended next steps your second line can act on.
Start from what you have
What changes, depending on where you are starting.
Read the card that matches your current stack.
If you run monitoring suites
You have detection and you have on-premise. What you do not have is root cause or an assistant.
- Alerting stays exactly where it is.
- Correlation and root cause get added on top.
If you run legacy log analytics
You centralized the logs and the bill went up with them. Root cause is an add-on, and sovereignty is partial.
- Flat pricing rather than ingest-based.
- Root cause built in rather than sold separately.
If you run cloud-only AIOps
You are paying per gigabyte to send network telemetry into someone else's tenant, with no on-premise option.
- The analysis comes back inside your perimeter.
- Sovereign-ready deployment becomes available.
Run your own evaluation
Questions worth asking every vendor on the shortlist.
Including us. A platform that cannot answer these live on your own data is selling you a table.
- How many systems does an engineer typically open during an incident?
- How long does it take to move from an alert to a probable root cause?
- How much time does the team spend manually correlating logs?
- How easily can engineers investigate incidents across different vendors?
- How much troubleshooting knowledge exists only in the heads of senior engineers?
- How many engineering hours go into investigating incidents every month?
- Are operational costs rising at the same rate as infrastructure complexity?
- Where would the evaluation sit if the data were not allowed to leave the network?
Keep reading
Where to go next.
Security and deployment
What "your data never leaves" means in practice.
Read the detail
Telco case study
Network observability inside a large multi-vendor carrier infrastructure.
Read the case study
The origin story
Why MIR Digital Solutions built an event intelligence platform.
Read the story
Book a demo
Compare it on your own incidents.
Thirty minutes with an engineer. Bring the incident that took eight hours.