MLOps & experiment tracking · WhyLabs, Inc. (discontinued operations in 2025; codebase open-sourced)

WhyLabs

Formerly a hosted AI-observability platform for monitoring model and data drift; the company has since shut down and open-sourced its stack.

Visit WhyLabs Alternatives

WhyLabs was a production model-monitoring and data-observability platform, not an experiment tracker — it profiled data statistically and watched deployed models for drift, data-quality issues, and anomalies without needing to store raw data. As of this writing, WhyLabs, Inc. has discontinued commercial operations and closed the hosted platform; the company released its full codebase as open source, including whylogs (its data-logging library) and LangKit (a toolkit for monitoring LLM inputs/outputs), which remain usable and maintained as community open-source projects. There is no longer a WhyLabs-branded commercial SaaS or support offering to evaluate. Readers comparing tools in this space should treat WhyLabs as a discontinued product and consider Evidently AI, Arize AI, or Fiddler AI for an actively supported commercial monitoring platform, or adopt whylogs/LangKit directly for a self-hosted, code-only approach.

At a glance

Vendor WhyLabs, Inc. (discontinued operations in 2025; codebase open-sourced)
Pricing model Open source + paid options
Free tier Yes
Deployment Self-hosted
Open source Yes (Apache-2.0)
Best for Developers who want the open-sourced whylogs/LangKit libraries rather than a supported commercial platform.

Pricing

The commercial WhyLabs platform has been discontinued; only the open-source whylogs and LangKit libraries remain, and they are free.

Pricing has not been verified yet — see the vendor's site.

Features

  • Statistical data profiling without storing raw data (whylogs)
  • Data and concept drift detection
  • LLM input/output monitoring (LangKit)
  • Anomaly detection on production data
  • Lightweight, open-source logging library
  • No hosted commercial dashboard (discontinued)

Integrations

Profile last reviewed September 21, 2026

Alternatives

Evidently AI Open-source and cloud model-monitoring tool that checks deployed ML/LLM systems for drift, data quality, and performance issues. Arize AI Hosted AI observability platform that monitors deployed ML models and LLM applications for drift, quality, and performance issues. Fiddler AI Hosted AI observability and guardrails platform for monitoring deployed ML models and LLM/agent applications.

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Terms to know

Data observability Continuous automated monitoring of pipelines and datasets to catch freshness, volume and quality problems early. Data quality The degree to which data is accurate, complete, consistent and fit for the purpose it is being used for. Anomaly detection Identifying data points or patterns that deviate significantly from expected or normal behavior. Concept drift A change over time in the underlying relationship between a model's inputs and the outcome it predicts. Data drift A change in the statistical properties of input data over time that can silently degrade a deployed model's accuracy. Data profiling Automatically scanning a dataset to summarize its structure, value distributions, and quality before it is trusted or modeled.

Related guides

How to choose an MLOps & experiment tracking tool "MLOps" covers five different jobs — tracking, monitoring, orchestration, serving, versioning — and most teams need more than one, not the biggest single tool.