3 AI SOC Platforms to Consider When a Copilot Isn’t Enough

AI copilots have earned a place in the SOC. They can answer questions quickly, help analysts write queries, summarize alerts, and draft reports.

For teams already working in Microsoft, CrowdStrike, or another large security ecosystem, having that assistance inside the console can save time. 

However, if an analyst still has to open each alert, decide what to investigate, prompt the copilot for help, interpret the answers, and determine what happened, the analyst remains the engine of the investigation. 

AI SOC platforms are designed to carry more of that investigative workload themselves.  

For buyers who already have a copilot, the question is how much work still falls to the analyst once an alert arrives.

Look at how far it can take an investigation, what it records along the way, and how much of your existing security stack it can reach. 

What Changes When the Copilot Stops Driving?

A copilot works well when there is a person there to direct it. An analyst asks a question, requests a query, or uses it to make sense of an alert. That can make individual investigations faster.

It does not necessarily solve the capacity problem when hundreds or thousands of alerts need attention.  

Gartner describes AI assistants as dependent on human input, while task-specific agents can handle more complex work from start to finish. 

Start with investigation depth. Can the technology decide what to check next as evidence emerges and keep going until it reaches a conclusion, or does the analyst still have to steer? 

It also needs to show its work. A useful alert summary is not the same as a record showing which systems were queried, what evidence was found, and how that evidence led to the verdict.

Another analyst may need to review the decision later, while auditors may want to know how it was reached. 

Most SOCs run tools from several vendors. Investigating a single alert can mean pulling evidence from the SIEM, EDR, identity provider, email platform, cloud environment, and threat intelligence sources.

A copilot built around one vendor’s ecosystem may not be able to reach everything an analyst needs. 

The following three platforms handle those requirements in different ways. 

Prophet Security: Carry the Investigation Through to a Verdict

Prophet Security is built around an agentic investigation model. Its AI SOC Analyst plans an investigation, gathers evidence across security tools, changes direction as it finds new information, and reaches a determination that can be audited step by step. 

The analyst does not have to keep prompting the next investigative step. The resulting verdict includes the queries, evidence, and reasoning used to reach it, while integrations provide access to evidence across a multi-vendor environment. 

In a copilot-led workflow, the analyst drives the investigation. The agentic model is designed to take on the investigation itself, addressing investigation depth, the evidence trail, and cross-stack access in the same platform. 

Dropzone AI: Autonomous Investigation Across Common Alert Types

Dropzone AI investigates alerts without an analyst having to prompt it through each step. It gathers and analyzes evidence across a slew of alert types, including phishing and identity, and records what it finds in an investigation report. 

For a phishing alert, for example, Dropzone can inspect headers, follow redirected URLs, analyze attachments, check reputation data, and assess the wider impact across email, endpoint, and identity systems.

Its identity investigations can pull information from IAM, identity provider, and other security data sources. 

For teams dealing with large phishing or identity queues, a useful test is how many of those alerts Dropzone can investigate without an analyst taking over. 

Command Zero: Put More Investigative Context in Front of Experienced Analysts

Command Zero combines encoded security expertise with LLM capabilities to help analysts work through deeper Tier 2 and Tier 3 investigations. 

Not every SOC wants to remove the analyst from an investigation. Some want experienced investigators to get to the relevant evidence faster while retaining human direction over complex cases. 

Command Zero is aimed further up the analyst chain, where experienced investigators are working through cases that require more judgment and context.

For buyers, that creates a different choice from fully autonomous investigation: whether the goal is to hand off more investigations or make the people conducting them faster. 

Make Vendors Prove What Happens on a Real Alert

A vendor demo should show what happens when a real alert arrives. A polished summary or an impressive chat interface can look convincing in a scripted demonstration without revealing how much work remains for the analyst. 

Bring four questions into that conversation: 

• For the last 10 alerts the platform closed, how many needed an analyst to step in before the investigation finished?
• Pull up the reasoning trail for one closed alert right now, not a summary, the actual step-by-step evidence chain.
• Of the tools already in the stack, name them, which does the platform pull from natively today, and which would need a custom connector?
• Run it against a live alert from the buyer’s own environment, right now, not a pre-built demo scenario.

Put the copilot you already have to the test against the same four questions. Any work still left with the analyst gives you something concrete to take into the next vendor conversation. 

Kirsten Doyle has been in the technology journalism and editing space for nearly 24 years, during which time she has developed a great love for all aspects of technology, as well as words themselves.

Her experience spans B2B tech, with a lot of focus on cybersecurity, cloud, enterprise, digital transformation, and data centre.

Her specialties are in news, thought leadership, features, white papers, and PR writing, and she is an experienced editor for both print and online publications. She is also a regular writer at Bora.