FortWatch.ai - 2026 Pricing, Features, Reviews & Alternatives

FortWatch.ai is a cloud-based, AI-first external attack surface management (EASM) platform built for small and medium-sized businesses, startups, DevOps teams, MSPs, and IT managers operating without a dedicated security operations center. The platform runs continuous scanners against internet-facing domains, IPs, and cloud accounts, covering vulnerability scanning with CVE detection and OWASP Top 10 coverage, SSL/TLS monitoring, DNS security validation, port monitoring, cloud bucket exposure detection, server hardening audits, and brand monitoring for lookalike and typosquat domains. Fully managed SaaS with no agents, no self-hosting, and no installation — assets are added by entering domains, IPs, or cloud account credentials, with the first scan achievable in minutes.

FortWatch.ai applies an AI layer to every finding, generating plain-English explanations of what each issue is, why it matters in the context of the specific asset, and step-by-step remediation guidance. AI-powered prioritization ranks findings by real-world exploitability and business impact rather than raw CVSS scores alone, reducing noise so non-security teams can act on the highest-risk issues first. False positive filtering further reduces raw scanner noise before findings reach the dashboard. A conversational AI interface allows users to interact with and navigate the platform via chat. All scanners are included on every plan with no feature gating, and transparent self-serve pricing starts at $99/month with no enterprise contract required.

The unified dashboard provides a single view of the entire external attack surface across web applications, infrastructure, and cloud environments. Multi-project workspaces allow MSPs to manage multiple client environments under one account with isolated data and unified billing. Real-time alerts are delivered via Slack, email, and webhooks with severity filtering, digest mode, quiet hours, and deduplication. SOC 2 and ISO 27001 compliance evidence collection is automated. Integrations include Slack, GitHub, Jira, AWS, Datadog, PagerDuty, Grafana, and Docker, with a REST API and webhooks available for custom workflows. Issue tracking supports findings-to-actions workflows with SLA deadlines, and reporting is available via PDF and CSV export.