AI Compliance Vendors

WhyLabs

The AI Observability Platform

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Last verified April 24, 2026

Quick facts: WhyLabs is an AI compliance vendor founded in 2019 and headquartered in Seattle, US. The vendor publicly documents coverage for SOC 2. Pricing is tiered. Profile last verified April 24, 2026, with every claim traceable to a cited public source.

About WhyLabs

WhyLabs provided an AI observability platform for monitoring machine learning models, data pipelines, and generative AI applications in real-time. Key differentiators included privacy-preserving data logging via open-source whylogs, LLM monitoring with langkit, drift detection, and low-latency threat detection without data movement. Targeted ML engineers and data scientists at Fortune 100 companies to AI startups in regulated sectors like financial-services and healthcare. Company discontinued commercial operations in 2025 following reported acquisition by Apple, open-sourcing its platform; tools remain available on GitHub.

Attestations held

Third-party security attestations and certifications WhyLabs documents on their own materials. These are point-in-time auditor opinions, not regulatory compliance. Always request the current report or certificate directly from the vendor before relying on it.

SOC 2 (Service Organization Control 2)

Attestation · United States (AICPA)

Certified

WhyLabs features

Capabilities WhyLabs markets publicly. Inclusion means the feature is documented on the vendor's site — not that it's best-in-class. Last verified April 24, 2026.

Model Monitoring

Production monitoring for performance, drift, data quality, and fairness regressions.

Drift Detection

Automated detection of distribution shift, feature drift, prediction drift, and performance degradation in deployed ML/AI models.

LLM Evaluation

Systematic testing of LLM outputs for correctness, relevance, safety, and consistency using automated scorers, rubrics, or human review.

Bias & Fairness Testing

Automated statistical testing for disparate impact across protected attributes, with audit-ready reports.

LLM Guardrails & Content Filtering

Runtime guardrails that block or redact unsafe prompts and responses in production LLM applications.

AI Model Inventory

Centralized registry of all AI/ML models in use across the organization, with ownership, lifecycle stage, and risk classification.

Integrations

Documented by WhyLabs in public product materials.

  • PyTorch
  • TensorFlow
  • scikit-learn
  • Apache Spark
  • Ray
  • OpenAI API

WhyLabs pricing

Contact for pricing

Free tier for 1 model; $100/month for 2 models, scaling per model up to enterprise at $8,333/month (AWS Marketplace listing).

Pros and cons of WhyLabs

Pros

  • Pioneered AI/LLM observability category with open-source foundation (whylogs, langkit).
  • Privacy-preserving monitoring without data leaving customer environment.
  • Tiered pricing with free tier and broad integrations including PyTorch, Spark, Ray.
  • SOC 2 Type 2 compliant for enterprise use.

Cons

  • Commercial operations discontinued in 2025 post-acquisition; no active support.
  • Narrower focus on observability vs full governance platforms.
  • Pricing listings may be outdated due to shutdown.
  • Limited public documentation on specific regulatory framework coverage beyond SOC2.

Frequently asked

What happened to WhyLabs commercial product?+

Discontinued operations in 2025; platform open-sourced on GitHub.

Is there a free tier?+

Yes, free for monitoring 1 model per AWS Marketplace.

What open-source tools remain?+

whylogs for data logging and langkit for LLM monitoring.

What industries did it serve?+

Financial services, healthcare, retail, manufacturing, logistics.

Sources

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