Compare Hyperproof vs. ValidMind

Compliance work eats engineering time. Hyperproof exists to give that time back by automating the parts of GRC that don't need a human: pulling evidence out of GitHub, Jira, ServiceNow, Snyk, and cloud storage on a schedule, running recurring tests against high-frequency controls, and kicking off a task automatically the moment something fails instead of waiting for the next audit cycle to find out. Under the hood, Hyperproof maps one control to 160+ frameworks (SOC 2, ISO 27001, HIPAA, NIST, and others), so a control tested once can satisfy several standards instead of forcing teams to rebuild the same work per framework. AI agents handle the first pass on evidence review and gap-flagging, leaving humans to make the actual judgment calls rather than hunting down documentation. Teams using it report cutting audit prep by roughly 350 hours a year, a 66% drop in duplicate controls, and about $150K saved annually on control orchestration. It also scales to messier org charts, with the ability to scope controls by business unit or entity instead of flattening everything into one program. Built in 2018 out of the Seattle area, Hyperproof is used by engineering and security-heavy orgs like Reddit, Fortinet, Appian, and Outreach that are tired of treating compliance as a manual, spreadsheet-and-email process and want it to run more like the rest of their infrastructure: automated, monitored, and auditable.

ValidMind stands out as the premier solution for organizations seeking to streamline the automation of testing, documentation, and risk management concerning AI and statistical models. This comprehensive platform offers a range of tools designed to assist data scientists, corporations, and risk or compliance professionals in pinpointing and documenting potential risks linked to their AI models, ensuring adherence to regulatory standards. With its integrated features, ValidMind simplifies the review process of risk areas across various teams' models, allowing organizations to effectively prioritize compliance and risk mitigation efforts. Furthermore, ValidMind promotes collaboration by breaking down information silos, thereby alleviating the complexities involved in sharing and working together on model documentation, validation reports, and risk assessments throughout the entire model lifecycle. By leveraging ValidMind, organizations can foster a culture of transparency and accountability in their AI practices.