HiddenLayer vs Promptfoo

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

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

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

Promptfoo

Build Secure AI Applications

Promptfoo is an open-source CLI and library for evaluating LLM prompts, models, RAGs, and agents through automated benchmarks and matrix comparisons, alongside red-teaming for security vulnerabilities like prompt injections, jailbreaks, PII leaks, and insecure tool use. It differentiates via developer-first local execution, CI/CD integration, and modular plugins covering 50+ attack types with community-driven threat intelligence. Targeted at developers and security teams in enterprises (127 Fortune 500 users), it supports self-hosting to avoid vendor lock-in. Enterprise adds collaboration, monitoring, SSO, and compliance dashboards. Acquired by OpenAI in March 2026 for integration into Frontier platform, remains open-source with SaaS/on-prem options.Promptfoo homepagePromptfoo docsPromptfoo pricing

Last verified April 24, 2026San Francisco, US

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: None documented in common.
  • Only HiddenLayer covers: EU AI Act, ISO/IEC 42001, NIST AI RMF
  • Shared capabilities: 1 of 10 listed.

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

At a glance

AttributeHiddenLayerPromptfoo
Founded20222024
HeadquartersAustin, United StatesSan Francisco, US
Employees51-20011-50
FundingSeries 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.$23.4M total (Series A, July 2025)
PricingEnterprise-only, contact sales for pricing. No public pricing listed on website.Contact for pricing
WebsiteVisit siteVisit site

Framework coverage

FrameworkHiddenLayerPromptfoo
EU AI ActPartial
ISO/IEC 42001Partial
NIST AI RMFPartial

Capabilities

CapabilityHiddenLayerPromptfoo
AI Model Inventory
Audit Evidence Collection
LLM Evaluation
LLM Guardrails & Content Filtering
LLM Red Teaming
Model Monitoring
Policy Management
Prompt Management
Risk Assessment Workflow
Third-Party AI Vendor Risk

Industries served

HiddenLayer

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

Promptfoo

  • Healthcare
  • SaaS & Technology

Integrations

HiddenLayer

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

Promptfoo

  • OpenAI API
  • Anthropic API
  • GitHub
  • GitLab
  • Jenkins

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