Cypago Cyber GRC Automation (CGA) Platform

Monitors deployed controls in real time to confirm they are operating effectively, surfacing control failures and weaknesses promptly rather than at point-in-time audits.

Continuously and automatically collects control evidence from connected tools to demonstrate compliance to auditors and regulators, replacing manual, point-in-time evidence gathering.

Maps measured controls to internal policies and external frameworks (NIST CSF, CIS, PCI DSS, DORA, ISO 27001) and crosswalks overlapping requirements to track compliance posture.

Ingests data from diverse security, IT, and business tools through agentless connectors into a central platform, the foundation that feeds continuous control measurement.

Applies AI and machine learning to assess control state, automate framework mapping, and surface insights from large volumes of control data.

Provides customizable dashboards and analytics that report control posture to auditors, the board, and regulators, supporting use cases such as SEC cyber disclosure and DORA readiness.

Continuously identifies assets that are missing a required control, such as endpoints without an EDR agent or systems outside vulnerability-scan scope, and quantifies control gaps across the asset estate.

Translates control posture into business-aligned cyber-risk reporting, enriching control gaps with business context and quantification so remediation is prioritized by impact.

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

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

Prepares audit-ready evidence packages and supports collaboration with internal and external auditors.

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

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

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

Provides a natural-language interface to query the GRC program and generate workflows, narratives, and reports, letting practitioners ask questions and draft content without building queries or templates by hand.

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.