How to run an AI SOC proof of value against the SOAR you have

A proof of value for an AI SOC platform answers one question: on your alerts, with your tools, does it reach the same conclusion your analysts would, and can you see why? It is not a feature tour. Vendors describe their strengths on their own sites, and our rankings summarise those. A proof of value tests the part no public page can show, which is how the platform behaves in your environment.

For a team that runs a playbook-based SOAR today, it also answers a second question: which alerts could leave the SOAR, and which should stay. Our migration guide covers the full move. This note covers the test that should come before it.

Pick three to five categories, not everything. Good candidates have enough volume to produce a sample in a few weeks, a clear record of what analysts decided, and a playbook you already run, so there is a baseline. Phishing reports, suspicious sign-ins and endpoint alerts are common choices because most AI SOC platforms in this guide name them. Dropzone AI, for example, lists phishing, endpoint, network, cloud, identity and insider threat alerts.

Include one category your playbooks handle badly. The case for an AI SOC platform rests on the long tail, where each alert needs different evidence, so the test should contain some of it.

In its most conservative mode, with no automatic response. Mate Security calls this Recommend only; Conifers describes starting with a human in the loop; Prophet Security offers response actions with your sign-off; 7AI describes approval gates. The platform investigates and proposes, your analysts decide, and your SOAR keeps running as it does today.

Give the platform read access to the same tools your analysts use for those categories, scoped to the minimum. Ask the vendor for its integration list before the test starts. Some publish counts (Prophet Security lists 200+, Intezer 100+, Dropzone AI 90+ across 14 categories, Torq 300); Mate Security names its integrations but does not publish a count, so confirm yours are covered.

• Agreement: for each category, how often the platform's verdict matched the analyst's final decision, and the cases where it did not.
• Evidence: whether each verdict shows what was checked and what was found, so an analyst could verify it without redoing the work.
• Misses: any alert the platform closed as benign that an analyst escalated. These matter more than the agreement rate.
• Analyst time: how long an analyst spent reviewing the platform's verdict compared with investigating from scratch, recorded by your team, not taken from vendor figures.
• Proposed actions: which response actions the platform would have taken, and whether your team would have approved them.

Vendor sites quote their own performance figures. Treat them as claims to test, not as targets. Your numbers from your alerts are the ones that matter for the decision.

Long enough to cover a normal range of alerts for each category, including a weekend and at least one busy period. Several vendors say onboarding is quick (Conifers says 2–4 hours; Mate says its Security Context Graph is built within 24 hours of integration), but a short onboarding does not shorten the time needed to collect a fair sample. Agree the end date and the success criteria with the vendor before you start.

• The pricing unit and how it scales with alert volume (see AI SOC pricing in 2026).
• Where data is processed and stored, and whether single-tenant or customer-tenant options exist.
• How autonomy is raised and lowered per category, and what happens when the platform's behaviour drifts. Mate says it rolls back to Supervised mode on drift.
• How existing playbooks are handled: translated (Mate Security describes translating SOAR playbooks into Gamebooks), rebuilt (Torq), or kept alongside (Dropzone AI, 7AI, Intezer).
• What the audit trail records for every action.

Write a one-page result per category: agreement, misses, evidence quality, analyst time and proposed actions. Categories with high agreement, no serious misses and good evidence are candidates to move, first in supervised mode. Categories with misses stay with the SOAR and the analysts. Then read the costs in order and decide whether to migrate, blend or stay.