10 Best SOAR Tools for Enhanced Cybersecurity

Ask a security operations team in 2023 what would fix their alert fatigue and most would have said "SOAR." Ask the same question in 2026 and you get a more complicated answer, because the category is quietly splitting in two, and a fair number of vendors have stopped using the term "SOAR" at all.

"SOAR was a little bit of a made-up term," Thomas Kinsella, co-founder of Tines, told TechTarget in April 2026. Tines has never called itself a SOAR vendor, despite showing up on most SOAR comparison lists; it describes its platform as AI-enhanced workflow automation instead. That rebrand isn't just marketing spin. It reflects a real architectural fork happening across the market this year, and it matters for anyone actually shopping for one of these tools right now.

The market, in numbers

Despite the naming confusion, the underlying spend keeps climbing. The SOAR market sat at USD 1.87 billion in 2025 and is forecast to reach USD 4.42 billion by 2030, an 18.8% CAGR, according to Mordor Intelligence's 2026 analysis. Software platforms held 64% of that revenue in 2024, while the services side, implementation, playbook customization, managed SOC operations, is actually growing faster, at a projected 20.8% CAGR through 2030.

Cloud deployment now dominates: 71% of SOAR revenue in 2024 came from cloud-based deployments, expanding at a 24.4% CAGR. And while large enterprises still hold 78% of total revenue, small and mid-sized organizations are the fastest-growing buyer segment, posting a 19.6% to 22.6% CAGR depending on which analyst firm you ask, largely because SaaS delivery and low-code interfaces have cut setup time from months to weeks.

A few specific drivers explain the sustained growth. SOAR implementations cut investigation cycles by as much as 75% and drive an 82% decrease in unplanned downtime, per Mordor's research. Globally, 3.4 million cybersecurity roles remain unfilled, a gap that widened 26.2% between 2021 and 2022 and hasn't meaningfully closed since. And the practical labor math is stark: Torq's AI-native autonomous SOC reportedly handles 95% of routine incidents without human intervention, which is exactly the kind of multiplier that makes automation budgets easy to defend internally, even when headcount is frozen.

The fork: workflow builders versus agentic AI SOC platforms

Here's where it gets genuinely interesting for buyers in 2026. The market has split into two distinct architectural bets, and picking the wrong one for your team's maturity level is the single most common mistake we see organizations make.

Workflow-automation platforms (Tines, Torq, Cortex XSOAR, Splunk SOAR, Swimlane Turbine) still require you to map out the logic yourself: if this indicator is malicious, then take this action. They've gotten faster and lower-code, but a human still designs the playbook.

Agentic AI SOC platforms (Prophet Security, and increasingly parts of Cortex XSIAM) remove the playbook requirement almost entirely. Instead of pre-built logic, an AI agent reasons through an investigation the way an analyst would: pulling EDR data, checking identity logs, correlating evidence, and reaching a conclusion, with a replayable audit trail showing exactly what it queried and why.

Kevin Schmidt, senior director analyst at Gartner, told TechTarget that this split explains a lot of SOAR's historical implementation pain. "Organizations struggled to implement SOAR for a number of reasons," he said. "You had to write code or scripts or use some sort of an interface to build executable blocks that you would link together." He added that the brittleness compounds over time: "With the nature of it being code, at the end of the day, it is sometimes very brittle."

Cody Cornell, CEO and founder of Swimlane, made a similar point about the human capital problem underneath legacy SOAR: using it effectively required someone fluent in incident response, security operations, threat intelligence, and the MITRE ATT&CK framework simultaneously. "Finding someone that was good at all that was hard," he said.

Where AI genuinely helps, and where it doesn't yet

The honest caveat, which too many vendor pitches skip, is that deterministic and probabilistic workflows are not interchangeable, and treating them as such creates new risk rather than removing it. "If you've got a security alert and you know the playbook it should follow, there's no reason it should be an AI agent responding," Kinsella said. "You should be relying on a deterministic outcome for something that you know is deterministic." He recommends reserving AI agents for genuinely probabilistic work: summarizing alerts, or evaluating incidents where severity is ambiguous.

There's also a cost dimension that's easy to underestimate before you've actually run the numbers. "The cost to do automation is much cheaper than AI tokens," Cornell noted, arguing that using AI to build automation pipelines, rather than running AI inference on every single alert, is the more sustainable path. Matt Rodriguez, director of service delivery at cybersecurity consultancy Phoenix Cyber, put a number on it: organizations seeing a fivefold ROI from traditional SOAR automation often find AI's unknown, usage-based cost less appealing by comparison. "We know what the real cost is to run automations with APIs and code within cloud infrastructure, and it's less than pennies on the dollar," he said.

Where the major platforms stand in 2026

The core players from a few years back are still around, but several have repositioned. Here's where the major platforms stand today.

Cortex XSOAR (Palo Alto Networks)

Still the heavyweight for organizations consolidated on the Palo Alto stack (Prisma, Cortex XDR, Strata). Its marketplace of pre-built integrations remains the largest in the category, and the "War Room" collaboration feature is genuinely strong for coordinating major incidents. The honest downside: deployment typically requires significant professional services, and ongoing maintenance can become a full-time role for a dedicated engineer.

Splunk SOAR

The native choice if your SOC already runs on Splunk Enterprise Security, offering tighter data-lake integration than any third-party tool can replicate. Its "Automation Broker" enables secure on-premise execution, useful for hybrid environments. Like XSOAR, it can suffer from "playbook drift," where logic quietly goes stale as environments change and nobody notices until an incident exposes the gap.

Tines

The clearest "no-code workflow, not SOAR" positioning in the market. Extremely flexible for connecting to arbitrary APIs, popular with engineers who want to build custom automations beyond pure security use cases. The tradeoff: it's a blank canvas. Tines doesn't know how to investigate a threat; your team has to design that logic from scratch.

Torq

Built to outpace legacy SOAR on raw speed, with parallel execution and browser-first design for high alert volumes. Copilot features help generate scripts, reducing some of the playbook-authoring burden. Still fundamentally a workflow engine underneath the speed improvements, so static logic can still miss a threat actor who changes tactics mid-campaign.

Swimlane Turbine

Evolved from standard SOAR into a low-code automation platform emphasizing data ingestion, capable of pulling in telemetry that never makes it into your SIEM. Strong for organizations that need custom applications built on top of security data, but it leans toward requiring Python expertise, which can be overkill for teams that just want straightforward alert triage.

Prophet Security

Representative of the agentic shift: rather than mapping investigation steps manually, its AI agents plan and execute investigations autonomously, using a "Glass Box" approach to keep every query and conclusion auditable. Purpose-built for security operations specifically, not general IT automation, and it's a newer entrant without the decade of integration depth that Cortex XSOAR has accumulated.

How to avoid buying a poor fit

A few practical warning signs still apply regardless of which architectural camp a tool falls into. Watch for platforms with genuinely limited automation and integration, meaning you'll end up manually shuttling data between systems that should talk to each other automatically. Watch for tools that lock you into vendor-only customization, since heavy reliance on professional services for every configuration change limits flexibility exactly when you need speed most. And watch for shallow reporting: if a tool can't tell you who did what, where, and when across every connected system, you'll struggle both with incident response and with proving compliance during an audit.

If you're not yet clear on how SOAR fits alongside SIEM in your stack, our deeper explainer on what SIEM actually does is worth a read before you evaluate vendors, since the two tools solve genuinely different problems that vendors sometimes blur together in sales conversations.

The decision that actually matters in 2026

Gartner's Schmidt offered maybe the most useful practical guidance in all of this: "You don't throw out your tool that is working just to go after the new splashy, shiny AI stuff." If your traditional SOAR deployment is delivering the fivefold ROI that Rodriguez describes, ripping it out for an unproven agentic platform is a real risk, not an obvious upgrade. The more common pattern emerging is supplementing existing SOAR with targeted AI, for change management, audit trails, and probabilistic judgment calls, rather than a wholesale replacement.

Schmidt's own prediction for where this goes: "Over time, SOAR is going to morph into the agentic software, AI SOC." That's likely correct directionally, but "over time" is doing real work in that sentence. For most organizations buying in 2026, the practical choice is still between a mature workflow platform you can fully audit and control, and a newer agentic platform that promises less manual playbook work in exchange for less predictability about exactly how it reaches its conclusions. Neither answer is wrong; it depends entirely on how much analyst expertise you already have on staff to supervise whichever model you pick.