Four guides for people who have to make the decision

Every security vendor now describes itself as an AI SOC. The label has stopped carrying information, which leaves a buyer to work out unaided whether a platform reasons about incidents or simply automates the steps around them. A vendor guide that answers that question only in its own favour is not useful to the person who has to sign the contract, and it does not survive contact with a proof of concept.

So these four are written as evaluation material rather than as sales material. They set out the tests, including the ones Spharaka would rather you did not think to run, on the reasoning that a buyer who evaluates carefully and chooses someone else was never going to be a good deployment anyway. The claims on the rest of this site are meant to be checked against these.

The AI SOC Buyer's Guide is the framework: how to separate a platform that reaches conclusions from one that ranks alerts more attractively, what questions distinguish them, and what to ask a vendor to demonstrate rather than describe. Start here if the category itself is still unclear.

Evaluating Autonomous Cyber Defence Platforms goes a level deeper into the specific distinction between assisted and autonomous. An assisted platform makes an analyst faster at work they were already doing; an autonomous one decides and acts. That is a testable difference, and the guide sets out what each should produce in a proof of concept, including what an honest failure looks like.

The AI SIEM Migration Guide is the operational one. SIEM migrations fail when they are run as replacement projects with a cutover date, because in month four the organisation discovers that a third of its detections depend on parsing quirks nobody documented. The guide sets out a phased approach that runs the two in parallel and moves detection families across in a defined order.

Choosing a Deployment Model treats deployment as an architectural decision rather than a procurement detail, because for an AI-native platform where the model runs determines what the platform can be asked to do. It covers cloud, hybrid, on-premises and air-gapped, and is candid about what each one costs you as well as what it buys.

The guides are the framework; the blog is where individual arguments are made at length. The comparisons are the most useful follow-on reading: agentic AI against SOAR automation, AI SIEM against traditional SIEM, autonomous defence against SOAR, and AI-assisted against AI-driven investigation. Each of those takes one distinction the guides make in a paragraph and gives it the space to be argued properly.

For readers whose concern is regulatory rather than technical, the data sovereignty and DPDP Act articles cover where telemetry may live and what that means for platform selection, which in practice constrains the shortlist more than any feature comparison does.