Table of Contents
- Introduction
- Prophet Security
- Bricklayer AI
- Conifers.ai
- Trellix – Helix XDR with AI
- Cisco – XDR and AI Assistant for Security
- Platform Comparison Table
- Conclusion
- Frequently Asked Questions
One key factor when selecting the AI SOC platform that’s right for your organization is how it thinks.
There are two schools of thought: agentic AI reasoning, and playbook automation. One allows for innovative autonomous thought for lifting heavier, more complex loads. The other allows for predictable efficiency and easy audits.
As with most things in life, the more tools in your belt, the better.
In this blog, we’ll investigate five AI SOC vendors that use either one, the other, or both of these methods to help you make your choice.
Prophet Security
For teams looking for a future-ready SOC partner that blends automation efficiency with transparent, reasoning-based decision-making. Prophet Security’s agentic AI SOC Platform combines playbook automation with explainable reasoning so that teams can work quickly while still understanding what their AI is doing.
Strengths
- Depth, quality, and accuracy of investigation: One of the core strengths of Prophet AI SOC Platform is the depth and accuracy of its investigations. It mirrors the investigation reasoning of a seasoned analyst but at machine speed.
- Agentic solution not limited by rigid playbooks: Prophet Security’s AI SOC platform is built on agentic AI “from the ground up,” with autonomous AI agents that gather intelligence, investigate, reason, and explain end-to-end actions, from initial triage, to investigation, to remediation. The platform doesn’t require prebuilt playbooks or prompting.
- Transparent Reasoning: Prophet AI SOC platform operates with transparent reasoning, showing the underlying evidence and ensuring every decision is explainable. so that SOCs can understand, audit, and influence agentic AI decisions.
Limitations
- Tooling Support Still Expanding: Prophet Security currently supports major vendors, with support for niche tooling growing based on customer needs.
Bricklayer AI
A multi-agent AI SOC platform, Bricklayer AI allows teams to deploy, orchestrate and govern multiple AI agents in one unified team. This allows for long-term memory sharing and increased flexibility.
Strengths
- Autonomous Task Execution: Agentic AI agents do more than make recommendations. They can perform security actions, integrating with current tools, enriching alerts, running playbooks, and more.
- Long-Term Memory: Key outputs, inputs, and decisions stored from previous workflows to reference for learning and context in future events.
Limitations
- Cost Tradeoff: Bricklayer itself mentions that deploying and training its multiple AI agents takes significant effort and infrastructure.
Conifers.ai
Conifers.ai offers an AI-native “Cognitive SOC” platform that adapts and refines its models over time based on your organization’s historical incident data, telemetry, and risk profile. Continuous learning is a strength.
Strengths
- Multi-Tenant Architecture: Makes it great for MSSPs that need to scale AI capabilities across a range of clients.
- Agentic AI: Agents ingest data across multiple sources (SIEM, historical context, knowledge bases, threat intelligence) to enrich and analyze alerts and ultimately decide which are real and which are false positives.
Limitations
- No Remediation: Does not offer end-to-end AI SOC remediation workflows like some other vendors. Closes false positives automatically, but does not otherwise provide active remediation (blocking, quarantining, patching).
Trellix Helix XDR with AI (Wise)
Trellix Helix XDR with AI combines its XDR telemetry with AI capabilities to detect threats, enrich alerts, identify false positives, correlate threats, and generate next-step suggestions for response.
Strengths
- Mature, Enterprise-Grade XDR Ecosystem: Leverages deep insights from a well-developed security stack, feeding AI models with mature and extensive threat intelligence.
- Integrates with Orchestration Tools: While it doesn’t provide remediation itself, Trellix integrates with outside orchestration tools to help teams hasten response.
Limitations
- Playbook Workflows: While offering low-code/no-code automation, Trellix does rely on pre-configured (though customizable) workflows created by analysts, rather than agentic AI.
Cisco XDR and AI Assistant for Security
Cisco XDR and AI Assistant for Security offers companies wide coverage across cloud, identities, network, and endpoints. It combines with agentic AI to provide investigation, triage, and even triggered response across the attack surface.
Strengths
- Instant Attack Verification: Leverages agentic AI to automatically analyze and correlate threats to vet whether they’re real—or false positives.
- Forensics Automation: Uses AI to trigger automatic collection of forensic evidence across endpoints (logs, registry, memory) based on context.
Limitations
- Enterprise-Level Cost: The start-up and maintenance cost of maintaining an enterprise-level XDR solution with AI Assistant may be cost prohibitive for smaller companies.
Platform Comparison Table
| AI SOC Platform | Best For | How It Uses Agentic AI | How It Uses Playbook Automation | Unique Selling Point |
| Prophet Security | Future-ready SOCs wanting reasoning + automation | Autonomous AI agents investigate, reason, explain end-to-end | Combines playbooks with AI reasoning | Transparent, explainable reasoning with actionable intelligence |
| Bricklayer AI | Teams needing multi-agent orchestration | AI agents execute tasks, enrich alerts, integrate tools | Runs playbooks autonomously | Multi-agent, long-term memory for learning and context |
| Conifers.ai | MSSPs or orgs needing adaptive AI SOC | Agents ingest multi-source data, enrich, decide alerts | Closes false positives automatically only | Continuous learning with multi-tenant scaling |
| Trellix Helix XDR with AI | Enterprises with mature XDR telemetry | AI detects threats, enriches alerts, identifies false positives | Integrates with orchestration tools; low/no-code workflows | Enterprise-grade XDR ecosystem feeding AI models |
| Cisco XDR + AI Assistant | Large orgs needing wide coverage | Agentic AI investigates, triages, correlates, verifies threats | Can trigger response playbooks automatically | Broad attack surface coverage with instant verification & forensics |
Conclusion
Agentic AI or playbook automation? The answer doesn’t have to be either-or. Companies can find benefits in predictable plug-and-play workflows as well as savvy, autonomous AI agents. Both can be combined to optimum effect.
But the security industry is definitely leaning towards a change. In its Agentic AI for Vendors article, Gartner predicted that “by 2028, one-third of GenAI interactions will involve autonomous agents.”
The shift towards agentic AI is here. Organizations looking to invest in AI SOC platforms should consider its future-proof implications when making their choice.
Frequently Asked Questions
- What is an AI SOC?
An AI SOC is a modern cybersecurity solution that leverages automation and artificial intelligence to make everyday SOC tasks like threat detection, investigation, and response faster, more accurate, and more effective.
- What are the benefits of agentic AI in the SOC?
The benefits of agentic AI in the SOC, as implemented through an AI SOC platform, include:
- Adaptive, dynamic decision-making vs. static scripts.
- Takes on ambiguous and complex tasks without hand-holding human involvement.
- Generates, tests, and reports on hypotheses.
- Gets better and conforms to your environment over time.
- Reduces threat investigation time by up to 90%.
- Will agentic AI SOCs replace human analysts?
No. As with all AI, to be truly effective and safe, AI SOCs must keep humans in-the-loop. As Gartner states, “[Security and Risk Management] leaders should focus the utility of AI and automation toward augmentation, not replacement.”
- What are the benefits of transparent SOC decision-making?
If analysts do not understand “black box” AI SOC decisions, they are less likely to follow them. The benefits of transparent SOC decision-making abilities, as enabled by transparent reasoning or evidence explainability, are that:
- Analysts get a clear picture of how AI models reached their conclusions; data points, steps, processes.
- Teams can audit gaps or errors in AI SOC logic early-on.
- Increases trust in AI SOC decisions because analysts can verify them.
An ardent believer in personal data privacy and the technology behind it, Katrina Thompson is a freelance writer leaning into encryption, data privacy legislation, and the intersection of information technology and human rights. She has written for Bora, Venafi, Tripwire, and many other sites.
