WhyLabs vs Deepchecks
Both compete in Observability & Monitoring. WhyLabs positions itself as “Privacy-preserving AI observability via open-source whylogs and LangKit (acquired by Apple)”, while Deepchecksleads with “Open-source-led testing, evaluation and monitoring for ML models and LLM applications”. The table below compares what each publishes.
Where WhyLabs pulls ahead
Teams seeking free, open-source, privacy-preserving ML and data monitoring via whylogs and LangKit, rather than a supported commercial product.
Where Deepchecks pulls ahead
Publishes support for SOC 2, GDPR, HIPAA, which WhyLabs does not. Data science and ML engineering teams wanting code-first, open-source-backed validation of models and LLM apps, with an enterprise upgrade path for production monitoring.
| Positioning | Privacy-preserving AI observability via open-source whylogs and LangKit (acquired by Apple) | Open-source-led testing, evaluation and monitoring for ML models and LLM applications |
|---|---|---|
| Category | Observability & Monitoring | Observability & Monitoring |
| Frameworks | None published | SOC 2, GDPR, HIPAA |
| Deployment | Open-source, SaaS, API | Open-source, SaaS, Cloud, On-prem, API |
| Built for | Data Science / ML | Data Science / ML |
| Founded | 2019 | 2021 |
| Headquarters | Seattle, Washington, USA | Tel Aviv, Israel |
| Ownership | Acquired by Apple (deal dated January 2025); commercial operations discontinued and founding team joined Apple; platform released as open source. No longer an independent vendor as of mid-2026. | Independent |
| Funding | Approximately $14M raised before acquisition, including a ~$10M Series A; backed by AI Fund, Madrona Venture Group, and Jeff Bezos. | $14M seed led by Alpha Wave Ventures |
| Pricing | Formerly freemium SaaS; now open-source only (whylogs, LangKit) with no commercial offering or vendor support | Free open-source core; commercial enterprise LLM Evaluation platform (pricing not public) |
| Key capabilities |
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| Integrations | Apache Spark, MLflow, Amazon SageMaker | OpenAI, Anthropic Claude, Amazon Bedrock, LangChain, CrewAI, NVIDIA, AWS SageMaker, Datadog |
| Notable customers | None published | None published |
| Best for | Teams seeking free, open-source, privacy-preserving ML and data monitoring via whylogs and LangKit, rather than a supported commercial product. | Data science and ML engineering teams wanting code-first, open-source-backed validation of models and LLM apps, with an enterprise upgrade path for production monitoring. |
| Limitations | No longer an independent commercial vendor - acquired by Apple in 2025 and operations discontinued; only the open-source projects remain, with no vendor support, SLAs, or active product roadmap. | Oriented toward technical ML/engineering users rather than non-technical GRC or legal teams, and its regulatory-framework mapping is lighter than dedicated AI-governance and compliance platforms. |
Which should you shortlist?
Choose WhyLabs if teams seeking free, open-source, privacy-preserving ML and data monitoring via whylogs and LangKit, rather than a supported commercial product.
Choose Deepchecks if data science and ML engineering teams wanting code-first, open-source-backed validation of models and LLM apps, with an enterprise upgrade path for production monitoring.
Neither is a substitute for a governance program. Whichever you pick, you still need people who can define the policies the tool enforces.
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