Teams evaluating SOC automation or an AI SOC platform tend to ask the same handful of questions, whichever vendor they talk to. We build one, so here are our direct answers, written so you can use them in your own evaluation.
What is an AI SOC platform?
An AI SOC platform combines security data collection, workflow automation and AI agents that triage alerts, enrich them with context and draft investigations for an analyst. Traditional SOAR relies on fixed playbooks; an AI SOC adds agents that reason over the alert, the asset and the user before recommending or taking an action. A useful working definition for buyers: software that reduces analyst time per alert without hiding how each decision was made.
Does it replace my SIEM or SOAR?
Usually not on day one. The first question to ask is whether the platform ingests from the tools you already run, such as your SIEM, EDR, identity provider, email security and cloud logs, through native integrations or an API. Most teams start by placing automated alert triage in front of existing tooling, measure the result, and only then decide what to consolidate. Be wary of any evaluation that requires a full migration before you see value.
How do we measure whether it works?
Agree the metrics before the trial starts, and record a baseline from your current SOC. The numbers that matter to most security operations teams are these:
- Mean time to detect (MTTD) and mean time to respond (MTTR) for real incidents.
- False positives closed automatically, and how many of those closures an analyst would have agreed with.
- Analyst time spent per alert and per investigation.
- Escalation accuracy: how often the alerts the platform escalates turn out to be true positives.
- Detection coverage mapped to MITRE ATT&CK techniques.
The most reliable test is to replay a sample of your historical alerts with known outcomes and compare the platform's verdicts with what your analysts concluded. That gives you an accuracy figure on your own data rather than a vendor's demo set.
How much autonomy should AI agents have?
Autonomy should be granted per action, not per platform. Enrichment, deduplication and evidence gathering are low risk and can run fully automated. Containment actions, such as isolating a host, disabling an account or blocking a domain, should sit behind a human-in-the-loop approval until you trust the results. Ask the vendor to show you approval gates, per-action permissions and how an action is reversed.
What about data, privacy and audit?
Security telemetry contains personal data and sensitive details about your environment, so these questions belong in the first call, not the contract review:
- Where is our data stored and processed, and can we choose the region?
- Which language models are used, where are they hosted, and is our data ever used to train them?
- Is every agent decision and action written to an audit log we can export?
- Can we produce evidence for auditors and regulators without screenshots and spreadsheets?
An audit trail matters beyond compliance. When an analyst disagrees with an automated verdict, the reasoning and the evidence behind it are what let you fix the cause rather than argue with a black box.
Where does detection engineering fit in?
Automation is only as good as the detections that feed it. If your rules are noisy, an AI SOC will triage noise faster, which helps, but tuning the source helps more. Ask whether you can write, test and version detections as code, whether open formats such as Sigma are supported, and whether triage outcomes feed back into detection tuning so false positives fall over time.
A short checklist for your trial
If you are about to evaluate SOC automation platforms, including ours, these steps keep the trial honest and comparable:
- Record baseline MTTD, MTTR, alert volume and analyst time per alert.
- Connect two or three existing data sources rather than migrating anything.
- Replay historical alerts with known outcomes and measure verdict accuracy.
- Start with automated enrichment and triage; keep containment behind approval.
- Test prompt injection with crafted alert content.
- Export the audit log and check that every action is explained.
- Review the results with the analysts who will use the platform every day.
Whichever platform you choose, the right one is the one that shows its working on your data. If you would like to run this checklist against Imperum, our module pages describe each part of the platform and how it connects to the tools you already have.