Hyperproof

Seattle compliance operations platform built around a common control set

Overview

Hyperproof is based in Seattle and was founded by Craig Unger, its chief executive, who says the product grew out of his frustration with managing high-stakes audits[13]. Rather than leading with automated cloud tests, Hyperproof is organised around compliance operations: it standardises control activities across frameworks and automates a common control set so one control can satisfy several requirements[12]. The risk module links control health data to risk registers and adds vendor risk tracking with consolidated reporting; platform security includes role-based permissions, multi-factor authentication, single sign-on via Azure (OIDC), JumpCloud and Okta (SAML), and a SOC 2 Type II report[12]. Named customers on its about page include OutSystems, Acuity International, Appian and Thales[13]. The pricing page describes modules but not plans or prices, routing buyers to a proposal request[12]. Hyperproof sits between start-up compliance automation tools and full enterprise GRC suites. Its limitations are that the company does not publish a founding date or customer count, and that its marketing gives less detail about automated infrastructure testing than vendors such as Vanta and Drata.

Hyperproof features

  • Common control set mapped across frameworks
  • Control health linked to risk registers
  • Vendor risk tracking
  • SSO via OIDC and SAML
  • Customer success team for ongoing support
  • 160+ pre-built frameworks
  • Common control set with automated mapping
  • 200+ evidence integrations (Hypersyncs)

Hyperproof pricing

No plans or prices are published; the page describes Compliance, Risk, Security and Support modules and links to a proposal request.

Hyperproof strengths and limitations

Strengths

  • Strong crosswalking between frameworks
  • Risk registers tied to control status
  • Enterprise SSO options
  • Named enterprise customers
  • Strong cross-framework control mapping
  • Large integration library

Limitations

  • No founding date or customer count published
  • Less emphasis on automated cloud configuration tests
  • No published prices
  • Fewer AI-governance frameworks advertised than newer rivals
  • No published pricing
  • Less depth in financial and operational risk

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