Secureframe

Uses AI agents to carry out GRC tasks with limited human direction, such as mapping requirements to controls, reviewing collected evidence, recommending control applicability, and triaging risks, going beyond fixed rule-based automation. Agentic maturity varies widely across products.

Supports configuration of assessment questionnaires, evidence collection workflows, approval routing, and report templates without professional services or platform code changes.

Automatically and continuously collects control evidence from connected systems for audit readiness.

Continuously tests and monitors control operation and flags failures across the environment.

Provides prebuilt control libraries mapped to frameworks such as SOC 2, ISO 27001, NIST CSF, PCI DSS and HIPAA.

Publishes customer-facing trust centers and compliance status reports.

Prepares audit-ready evidence packages and lets external auditors and certification bodies run the audit inside the platform through role-based access, managing information requests, evidence review and findings in one place, with partner audit firms able to deliver the engagement end to end.

Provides connectors to cloud, identity, HRIS, MDM and ticketing systems to automate evidence collection.

Manages security policies and collects employee attestations to support compliance.

Maps controls across multiple frameworks and crosswalks overlapping requirements to reduce duplicate work.

Collects control evidence from CI/CD pipelines and code repositories, such as peer review on merged changes, pipeline security checks and deployment approvals, and can fail a pipeline stage when a change breaks a compliance policy, so that frequently releasing DevOps teams stay continuously audit-ready without manual screenshots.

Generates environment-specific remediation steps for failing controls and tests, such as infrastructure-as-code or command-line fixes for a cloud misconfiguration, and answers follow-up questions in context, so that engineers can close findings without translating a control requirement into a technical fix themselves.

Drafts and revises the policies, procedures and other written requirements a framework demands using generative AI, tailored to the organization and editable in place, so that teams do not start from a blank page or a generic template download.