Credo AI vs HiddenLayer

Side-by-side comparison of framework coverage, pricing, capabilities, and target customers. Last verified recently.

Canonical URL: https://aicompliancevendors.com/compare/credo-ai-vs-hiddenlayer

Credo AI

Context-driven AI governance for regulated enterprises.

Credo AI is an AI governance platform founded in 2020 and headquartered in San Francisco. The platform helps enterprises operationalize AI governance through a centralized model registry, guided impact assessments, policy packs mapped to regulations like the EU AI Act and NIST AI RMF, and evidence collection for audit. Credo AI has been cited as an NIST AI RMF contributor and has raised approximately $41.3M total, with a $21M round in July 2024 at a reported $101M post-money valuation.

Last verified April 21, 2026San Francisco, United States

HiddenLayer

The most comprehensive security platform for AI

HiddenLayer is an Austin, Texas-based AI security company founded in March 2022 by experienced cybersecurity and machine learning professionals. The company provides a comprehensive AI Security Platform covering AI Discovery (automated inventory), AI Supply Chain Security (model scanning for embedded threats), AI Attack Simulation (red teaming), and AI Runtime Security (guardrails and active threat response). The platform is designed to be non-invasive — protecting models without requiring access to raw training data — and integrates with CI/CD, MLOps, data pipelines, and SIEM/SOAR tools. HiddenLayer is recognized by Gartner as a Cool Vendor for AI Application Security. The company raised $50M in Series A in September 2023, the largest Series A for an AI-focused cybersecurity company at that time, led by M12 (Microsoft's Venture Fund) and Moore Strategic Ventures. Customers include enterprises in financial services, US federal government, and technology. Named endorsers include the CISO of the NFL and the former CISO of AIG.

Last verified April 22, 2026Austin, United States

What the data shows

We haven't published an editorial verdict on this pair yet. The comparison below is built from public vendor materials and our taxonomy — no editorialized ranking.

  • Shared framework coverage: EU AI Act, ISO/IEC 42001, NIST AI RMF
  • Only Credo AI covers: Colorado AI Act, NYC LL 144
  • Shared capabilities: 7 of 11 listed.

Want our editorial take? Email the editors or read our methodology.

At a glance

AttributeCredo AIHiddenLayer
Founded20202022
HeadquartersSan Francisco, United StatesAustin, United States
Employees51-20051-200
Funding$41.3M total (Series B, July 2024)Series A, $50M raised (September 2023), led by M12 (Microsoft's Venture Fund) and Moore Strategic Ventures, with participation from Booz Allen Ventures, IBM Ventures, Capital One Ventures, and Ten Eleven Ventures. Prior seed of $6M (April 2023). Total raised: $56M.
PricingEnterprise-only; typical engagements start in the mid-five figures annually.Enterprise-only, contact sales for pricing. No public pricing listed on website.
WebsiteVisit siteVisit site

Framework coverage

FrameworkCredo AIHiddenLayer
Colorado AI ActFull
EU AI ActFullPartial
ISO/IEC 42001FullPartial
NIST AI RMFFullPartial
NYC LL 144Full

Capabilities

CapabilityCredo AIHiddenLayer
AI Model Inventory
Audit Evidence Collection
Bias & Fairness Testing
Explainability
LLM Guardrails & Content Filtering
LLM Red Teaming
Model Monitoring
Policy Management
Regulatory Intelligence
Risk Assessment Workflow
Third-Party AI Vendor Risk

Industries served

Credo AI

  • Financial Services
  • Healthcare
  • Insurance
  • Government & Public Sector
  • Employment & HR
  • Education
  • Defense & National Security

HiddenLayer

  • Financial Services
  • Government & Public Sector
  • Defense & National Security
  • SaaS & Technology

Integrations

Credo AI

  • AWS SageMaker
  • Azure ML
  • Databricks
  • Snowflake
  • MLflow
  • Jira
  • ServiceNow
  • Slack
  • GitHub

HiddenLayer

  • AWS SageMaker
  • Azure ML
  • Databricks
  • GitHub
  • OpenAI API

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Editorial independence: This comparison is free and was not paid for by either vendor. See our methodology.