Best SOAR Platforms 2026

Security Orchestration, Automation and Response (SOAR) platforms automate security workflows by connecting multiple security tools and executing pre-defined playbooks in response to security events. A SOAR receives alerts from a SIEM, enriches them by querying threat intelligence feeds and asset databases, and can execute response actions like blocking IPs, isolating endpoints, or creating tickets.

For most SOC automation use cases, no. AI SOC platforms like ManySignal include built-in automation that covers alert enrichment, investigation, and response actions. Traditional SOAR is most valuable for complex, long-running enterprise IT workflows (HR offboarding integrations, IT service desk automation) that extend beyond pure SOC operations.

SOAR executes playbooks — predefined workflows designed by human engineers. If the situation matches the playbook conditions, it follows the prescribed steps. Agentic AI reasons about the situation: it can deviate from a template based on evidence, take unexpected investigation paths, and explain why it made each decision. SOAR is rule execution; agentic AI is reasoning.

Most SOC teams start with 10–20 core playbooks covering their top alert types: phishing triage, credential abuse, malware isolation, cloud misconfiguration notification, and user risk escalation. Many SOAR deployments grow to hundreds of playbooks, which then become a maintenance burden. AI-native platforms reduce playbook dependence by handling investigation reasoning directly.

Core SOAR integrations: SIEM (alert source), EDR (endpoint response actions), identity provider (account suspend/enable), ticketing (Jira, ServiceNow), email (phishing remediation), firewall/network (IP block), threat intelligence (enrichment). Secondary: vulnerability scanner, CMDB, communication platforms (Slack/Teams for approvals).

SOAR licensing is often significant, but the larger cost is human time: SOAR engineering resources to build and maintain playbooks, integration work to connect new tools, and operational overhead when playbooks break due to API changes in connected tools. Platforms that minimise the playbook maintenance burden (through AI assistance or pre-built connectors) have meaningfully lower TCO.

Yes, but should they? Best practice is to require human approval for high-impact actions. Most enterprise SOAR platforms support approval workflows: the automation proposes an action (suspend user account), sends an approval request via Slack or email, and waits for analyst confirmation before executing. This human-in-the-loop pattern applies to endpoint isolation, firewall blocks, and user account changes.

Key SOAR ROI metrics: automation coverage rate (% of alerts handled without human touch), mean time to response for automated vs. manual alerts, analyst hours reclaimed per week, false positive rate in automated closures, and playbook reliability rate (% of playbook runs that complete without error). Set these baselines before deployment to measure impact.

No-code or low-code visual builders (Tines, Torq) allow analysts who don't write code to build and modify automation workflows. Look for: drag-and-drop action blocks, pre-built template libraries, natural language playbook generation (AI-assisted), and the ability to test playbooks against historical alerts before deploying them live.

Not dead, but evolving. Traditional SOAR as a standalone platform is being absorbed by AI SOC platforms (which include automation natively) and by more accessible no-code tools (Tines, Torq). Pure-play SOAR vendors are differentiating on enterprise IT automation breadth (beyond SOC use cases) and on case management for complex incident response programs.