AI agents that investigate alerts on their own have gone from novelty to standard feature in the agentic SOC. The sale now turns on authority, and buyers want to know how much of it they're handing over.
Buyers want agents on Tier 1 work but hesitate to deploy them. In a Strike48 survey of 100 enterprise CISOs and mid-market security leaders, 84% said AI agents should be doing Tier 1 work, yet only 36% had one running in production. Distrust of agent outputs was the top barrier at 52%. Gartner's 2026 Hype Cycle for Security Operations places AI SOC agents at the Peak of Inflated Expectations, which fits the distrust buyers report.
Every platform on the market now has to show what its agent can see and what it's allowed to do with it.
Data and authority now set vendors apart
Across the ten platforms reviewed here, most describe some form of approval control. What separates them is how much of an organization's data the agent can reach and who sets the limits on what it does with it.
Fernando Montenegro of Futurum reached a similar view in his analysis of Zscaler's Agentic SOC launch. "The agents themselves are now table stakes," Montenegro wrote. In his reading, the edge belongs to the vendor whose telemetry gives agents the most to work with and whose data can verify an agent's conclusions.
Strike48's own research points the same way. In its survey, 84% of respondents said their current tools cannot reach all of their log data for investigations.
Strike48's, President and Co-founder, Tim Leehealey sees the same shift from the buyer's side. "Investigations are easy to demo now. Where platforms differ is in reaching the data an agent needs without asking a team to migrate everything first."
The profiles that follow sort the ten platforms into three groups. Five put agents on top of the tools a team already runs, four build on telemetry they already hold, and one grew out of an automation engine. Each profile covers what the platform reaches, how it limits its agents and what evidence supports it.
Five platforms sit on top of the security stack a team already runs
These five add agents on top of the SIEM, EDR and cloud tools a team already owns. They set themselves apart on control and on who does the work, with Radiant keeping an analyst on every verdict, Prophet and 7AI pairing agents with vendor-staffed services, and Strike48, 7AI and Dropzone AI working with data where it already sits.
Strike48
Strike48's President and Co-founder,Tim Leehealey points to what teams get out of the box. "Strike48 ships pre-built agent packages for common investigations, each with approval gates and an audit trail. Teams choose which actions run on their own, customize the packages or build their own, and read the record of every step before they widen an agent's authority."
Strike48 searches data in place across more than 300 systems, including SIEM, observability, ticketing and identity tools, connected by API or MCP. The platform page describes multi-tenant isolation, with per-tenant namespaces, quotas, role-based access control and separate secrets. Strike48 also sells the platform to MSSPs. The approach pairs approval gates, which speak to the distrust buyers report, with in-place search, which spares teams a data migration.
7AI
7AI describes agents that detect, investigate, respond and hunt across the SOC while humans stay in the loop. Its Federated SIEM is pitched as data queried where it lives, investigations show their reasoning, and response can be guided or automatic. The company also sells PLAID ELITE, a managed service in which its experts run the platform around the clock. The product pages describe the human role but don't detail how approval limits are configured. A customer testimonial on the site reports an 80% reduction in Tier 1 analyst time, a vendor-selected claim.
Dropzone AI
Dropzone AI investigates alerts end to end across SIEM, EDR and cloud tools and explains its reasoning in plain English. The company says it has 90+ integrations, needs no data migration or log normalization, and keeps a full audit trail of every question asked and tool queried. It also offers an AI Threat Hunter and an AI Threat Intel Analyst. Dropzone AI cites 5x faster MTTR and more than 300 organizations, both vendor figures, and prices by capacity without listing rates. It shows the add-on approach in its plainest form, with agents working over a SIEM and EDR the team already owns.
Prophet Security
Prophet Security covers alert triage and investigation, response, threat hunting and detection engineering. It says its determinations can be audited and that response runs through scoped Agent Actions, either autonomously or with the team's sign-off. It lists 200+ integrations but publishes no pricing or deployment figures on its homepage. Like 7AI, Prophet pairs its agents with a vendor-staffed service, here a 24x7x365 human-in-the-loop team, which suggests some buyers want the vendor to supply analysts as well.
Radiant Security
Radiant Security's documentation describes a pipeline that classifies, enriches, plans and executes for each alert, then returns a verdict with the tasks, questions and queries behind it. Analysts accept or override each verdict, and the platform recommends alerts for escalation without opening cases on its own. Analyst review can be required before automated response actions such as disabling users, isolating hosts and blocking IPs. Radiant also includes a data lake, stored in its cloud or the customer's AWS S3 bucket, and lists 100+ connectors. The docs define a tenant as an isolated account but don't say how MSSPs manage several. Radiant sits at the cautious end of this group, with an analyst ruling on every verdict.
Four platforms bet the best agent runs on telemetry its vendor already holds
The next four take the other route and argue that an agent works best on data its vendor already controls. Buyers who go this way are committing to that vendor's stack along with the agent.
CrowdStrike Charlotte AI
CrowdStrike's latest release has Charlotte AI dispatch specialized agents in parallel across endpoint, identity, SaaS, cloud and network data. The agents share one memory of the environment and reach a single conclusion with visible reasoning. Customers set the autonomy level for each workflow, from human approval to fully autonomous execution. CrowdStrike says every action is bounded, user-authorized and logged and that Charlotte AI is ISO 42001-certified for AI governance. The company also says it connects third-party agents through bidirectional MCP.
The release gives no general availability date and tells customers to base purchases on currently available features. The company's page stresses data native to its own platform, so teams running another EDR should test how much of an investigation depends on it.
SentinelOne Purple AI
SentinelOne has opened Purple AI Agentic Investigation to all customers. Investigations start on their own when a threat crosses a defined threshold, and each verdict includes an auditable evidence chain. Customers set autonomy through an adjustable human-in-the-loop setting, and activation is admin-controlled, role-based and reversible. The agents run on telemetry already in the platform, including endpoint, identity, cloud and third-party data, and consume Singularity Credits. The release gives no performance figures or credit allotment, so buyers have to size their own investigation volume to work out cost. Credit-based pricing makes SentinelOne the clearest case of cost scaling with agent activity.
Zscaler Agentic SOC
Zscaler announced its Agentic SOC and says it's available globally. Specialized agents handle triage, root-cause investigation, verdicts and response workflows. They draw on inline telemetry from what the company says are 750 billion daily zero-trust transactions, plus what it calls the world's largest decoy mesh network. Zscaler partnered with Anthropic and OpenAI for the underlying models, and Red Canary supplies human expertise for threat hunting. The announcement describes autonomous agents and closed-loop remediation but no approval gates or sign-off requirements. Futurum's analysis flagged three open questions about the design. Inline traffic lacks asset ownership and identity context, investigation data goes to outside model providers, and token costs may rise with investigation depth.
Exaforce
Exaforce builds its agentic SOC on a unified data layer and a real-time knowledge graph, and describes its data platform as built to replace the SIEM. Its Exabots cover detection, triage, investigation and response, with response described as automated actions under analyst oversight. It also offers an MDR service and a product for monitoring AI agents. Replacing the SIEM means moving security data, so teams keeping their current one should test how the pieces separate. Exaforce makes the most direct version of the data bet, because the agent and the data store ship as one product.
One platform grew agents out of an automation engine
Torq
Torq started in automation and added agents on top. Its AI SOC platform uses an agentic orchestrator, Socrates, to coordinate HyperAgents across triage, investigation and response, while a deterministic hyperautomation engine handles repeatable, high-volume work. The platform is MCP-native, acting as both host and client, and investigations are documented in Torq Case Management. Torq says Gartner named it the company to beat in a recent report, though the full report is available only to Gartner clients. Its page names an MSSP customer but describes no multi-tenant controls. The design answers the authority question structurally, by keeping repeatable work out of the agent's hands.
Agents earn authority through verification and accountability
Distrust of agent outputs is the top barrier buyers report, which makes verification and accountability the way an agent earns its authority. Sayali Paseband, Cybersecurity Advisor at Verisk, puts the standard in terms of evidence. "AI will earn enforcement authority the same way humans do: through accountability and evidence," Paseband says. "For an AI, this requires high-integrity inputs, constrained decision domains with predictable outputs, and complete auditability so its actions can be validated."
That standard also answers the "AI washing" and "agent washing" that Gartner warns about in its Hype Cycle. Gartner advises buyers to pilot rigorously and demand transparency. In Paseband's terms, that means a vendor can show the inputs behind a decision, the limits on what an agent may decide and a complete record of what it did.
Buyers can turn the same scrutiny on the vendor. Ralph Hogaboom, CISO at the Washington State Department of Natural Resources, treats a vendor's agentic claims as a reason to look harder. "I have some strong questions about any suppliers or partners that are telling me they're deploying agentic AI," Hogaboom says. "I'm going to want to take a lot closer look at your stack and how you protect and do business."
Proof of agent decisions will decide which platforms last
Any of these ten platforms can work an alert. The test comes when the agent gets one wrong and someone has to explain why. Buyers can run that test before they sign, with a pilot beside the current process that scores the platform against analysts' own verdicts and asks the vendor to reconstruct a decision picked at random. The result shows how much authority the agent has earned on the team's own alerts.
"Buyers shouldn't have to trade reach for control. The platforms that last will be the ones that work across all of a team's data, stay inside the limits that team sets, and can show what their agents decided and why," says Strike48's President and Co-founder,Tim Leehealey.
Frequently asked questions
What are the best agentic SOC platforms in 2026?
No single platform is best for every team. This report compares ten: Strike48, 7AI, Dropzone AI, Prophet Security, Radiant Security, CrowdStrike Charlotte AI, SentinelOne Purple AI, Zscaler Agentic SOC, Exaforce and Torq. The right fit depends on the SIEM and tools already in place and on how much autonomy the team will allow.
Which agentic SOC platform is best for MSSPs?
Strike48 documents per-tenant namespaces, quotas, role-based access control and separate secrets, and it has a page aimed at MSSPs. Dropzone AI, 7AI and Radiant also describe MSSP use, though Radiant's documentation doesn't detail multi-tenant management. Ask each vendor how tenant data and agent settings stay separate.
How do agentic SOC platforms handle human approval?
The controls differ by vendor. Radiant has analysts accept or override each verdict, Prophet runs response actions autonomously or with sign-off, and CrowdStrike lets customers set the autonomy level for each workflow. SentinelOne offers an adjustable human-in-the-loop setting, and Strike48 says teams choose which actions need approval. Ask for these settings per workflow and per asset.
Are AI SOC agents mature?
Not yet for most teams. Only 36% of the leaders in Strike48's survey had an AI agent running in production, and 52% named distrust of agent outputs as the top barrier.
