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WhyLabs

  • What it is:WhyLabs is an AI observability platform that monitors machine learning models, data pipelines, and generative AI applications for quality, performance, security, and issues like drift and bias.
  • Best for:Data scientists and ML engineers, Small and growing ML teams, Organizations prioritizing data privacy
  • Pricing:Free tier available, paid plans from $50-$125 per month per model
  • Rating:72/100Good
  • Expert's conclusion:WhyLabs pioneered important concepts in AI Observability and is no longer commercially available; use only the open-source components for non-critical self-hosted needs.
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Reviewed byMaxim Manylov·Web3 Engineer & Serial Founder

What Is WhyLabs and What Does It Do?

Developed an AI-based Observability Platform (WhyLabs) to monitor Data Quality & Machine Learning Model Quality, Performance, Security to prevent issues in Production. The company was incubated at the Allen Institute for Artificial Intelligence. Industries that used WhyLabs include Finance, Healthcare, Logistics, Retail & Manufacturing. The company is no longer in operation due to being fully acquired by Apple in 2025.

Acquired
📍Seattle, WA
📅Founded 2019
🏢Private
TARGET SEGMENTS
Financial ServicesHealthcareLogisticsRetailManufacturing

What Are WhyLabs's Key Business Metrics?

📊
2019
Founded
📊
$14M
Total Funding Raised
📊
Series A ($10M)
Latest Funding Round
👥
Trailblazing enterprise customers
Customers

How Credible and Trustworthy Is WhyLabs?

72/100
Good

Developed a successful product in AI Observability backed by VCs, received Industry Recognition but the company has been shut down since acquisition therefore no Ongoing Support or Development exists.

BREAKDOWN
Product Maturity80/100
Company Stability40/100
Security & Compliance75/100
User Reviews65/100
Transparency85/100
Support Quality30/100
TRUST SIGNALS
Incubated at Allen Institute for AIRaised $14M from reputable VCsOpen sourced complete platform including whylogs and langkitAcquired by Apple (assets/team)

What is the history of WhyLabs and its key milestones?

2019

Company Founded

Co-Founders include Alessya Visnjic, Andy Dang, Maria Karaivanova, Sam Gracie. WhyLabs was incubated at the Allen Institute for AI located in Seattle.

2021

Series A Funding

Received $10 Million in Series A Funding which brings the companies Total Funding to $14 Million.

2023

AI 100 Recognition

Recognized as one of the Top Most Promising AI Startups on the CB Insights AI 100.

2025

Acquired by Apple

Apple acquired WhyLabs' Assets, Team, Technology. WhyLabs ceased Independent Operations.

Who Are the Key Executives Behind WhyLabs?

Alessya Visnjic— CEO & Co-founder
Led WhyLabs from Inception through Defining the Category of AI Observability and through Acquisition by Apple.
Andy Dang— CTO & Co-founder
Technical Leader Responsible for Platform Architecture (whylogs, langkit Open Source Projects).
Maria Karaivanova— COO & Co-founder
Operational Leadership Scaled Business to Serve Enterprise AI Teams across Multiple Industries.
Sam Gracie— CPO & Co-founder
Product Visionary Shaped the AI Control Center & LLM Monitoring Capabilities.

What Are the Key Features of WhyLabs?

✨
AI & Data Observability
Continuously Monitors Data Quality, Model Performance, AI Application Health with Real-Time Alerts.
🔒
LLM Security & Responsible AI
LangKit Toolkit for Monitoring and Securing Large Language Models While Preserving Privacy.
✨
Privacy-Preserving Logging
WhyLogs Open Standard Enables Lightweight, Privacy-Preserving Data Logging for AI Systems.
✨
Model & Data Drift Detection
Automatically Detects Data Drift, Model Degradation, Performance Issues.
✨
Enterprise-Scale Monitoring
Designed for Mass Scale Across Financial Services, Healthcare, Logistics, Retail.
✨
Actionable Alerts
Real-Time Notifications Enables Rapid Response to Data Quality Issues and Model Failures.

What Technology Stack and Infrastructure Does WhyLabs Use?

Infrastructure

Cloud SaaS platform (specifics not disclosed)

Integrations

ML PipelinesLLM ApplicationsData Platforms

AI/ML Capabilities

AI observability platform with LLM monitoring, data drift detection, privacy-preserving whylogs logging, and langkit for LLM security

Inferred from product descriptions; specific languages/frameworks not publicly detailed pre-shutdown

What Are the Best Use Cases for WhyLabs?

ML Engineering Teams
Track your model’s performance, identify when it begins to deviate from its expected behavior, and receive actionable alerts regarding your AI system in a production environment
LLM Application Developers
Use an open source language kit (langkit) to ensure your practice is secure and responsible as you preserve user/ customer privacy using your AI application
Data Science Teams
Utilize whylogs to provide lightweight, privacy-preserving data logging for each phase of your ML pipeline
Financial Services AI Teams
Monitor the AI application used to process sensitive financial information using enterprise-level observability capabilities
NOT FORHealthcare AI Operations
Available open source tools are lacking guaranteed HIPAA compliance or ongoing vendor support
NOT FORTeams Needing Commercial Support
No longer supported by the company; no vendor support, SLA’s or commercial licenses available

How Much Does WhyLabs Cost and What Plans Are Available?

Pricing information with service tiers, costs, and details
☐Service$CostℹDetails🔗Source
Starter$0ML and Data Monitoring for individualsG2.com
Expert$50-$125 per month per modelFor small and growing teams, cloud-based, scales with features and segments monitoredTrustRadius, G2.com
Enterprise$100+ per month per modelCustom enterprise features including RBAC, SAML SSO, dedicated supportTrustRadius
Starter$0
ML and Data Monitoring for individuals
G2.com
Expert$50-$125 per month per model
For small and growing teams, cloud-based, scales with features and segments monitored
TrustRadius, G2.com
Enterprise$100+ per month per model
Custom enterprise features including RBAC, SAML SSO, dedicated support
TrustRadius

How Does WhyLabs Compare to Competitors?

FeatureWhyLabsArize AIFiddler AI
Core FunctionalityData/model monitoring, drift detection, LLM observabilityML observability, feature storeExplainable AI, model monitoring
Pricing (starting)$0 free tier, $50+/mo per modelCustom enterprise pricingCustom enterprise pricing
Free TierYes (Starter)Limited trialNo
Enterprise FeaturesSOC 2 Type II, RBAC, SSOYesYes
API AvailabilityYes (ingestion API)YesYes
IntegrationsAzure, Sagemaker, Spark, Pandas, Kafka, RayExtensive ML platformsMLflow, Databricks
Support OptionsCommunity, enterprise priorityEnterprise supportEnterprise support
Security CertificationsSOC 2 Type IISOC 2SOC 2
Core Functionality
WhyLabsData/model monitoring, drift detection, LLM observability
Arize AIML observability, feature store
Fiddler AIExplainable AI, model monitoring
Pricing (starting)
WhyLabs$0 free tier, $50+/mo per model
Arize AICustom enterprise pricing
Fiddler AICustom enterprise pricing
Free Tier
WhyLabsYes (Starter)
Arize AILimited trial
Fiddler AINo
Enterprise Features
WhyLabsSOC 2 Type II, RBAC, SSO
Arize AIYes
Fiddler AIYes
API Availability
WhyLabsYes (ingestion API)
Arize AIYes
Fiddler AIYes
Integrations
WhyLabsAzure, Sagemaker, Spark, Pandas, Kafka, Ray
Arize AIExtensive ML platforms
Fiddler AIMLflow, Databricks
Support Options
WhyLabsCommunity, enterprise priority
Arize AIEnterprise support
Fiddler AIEnterprise support
Security Certifications
WhyLabsSOC 2 Type II
Arize AISOC 2
Fiddler AISOC 2

How Does WhyLabs Compare to Competitors?

vs Arize AI

Whylabs’ TCO for infrastructure will be less expensive than Arize for companies monitoring 10+ models and Whylab’s is free for some models while Arize is more valuable for money spent per feature; WhyLab’s agent never moves data.

If you need cost-effective and privacy focused monitoring select WhyLab, if you require a feature rich enterprise deployment for all of your AI model monitoring select Arize.

vs Fiddler AI

WhyLab’s focus is on providing a simple way to perform lightweight data profiling and provides extensive platform integration support versus Fiddler’s focus is on explainable AI and providing the best overall solution for the customer. The price point for WhyLab is also significantly less expensive per model.

Select WhyLab for general ML observability, select Fiddler for use cases requiring high levels of explainability.

What are the strengths and limitations of WhyLabs?

Pros

  • We offer competitive pricing – our prices are the cheapest of the competition with the most features included.
  • Data Ingestion is very easy - we have native support for BigQuery, Databricks, Spark with data profiling.
  • We are privacy preserving – we do not move or duplicate data during analysis.
  • Our system performs well - we profile data quickly due to our lightweight profiling methodology.
  • We are flexible – monitors can be defined using JSON and can be version controlled.
  • We have broad integrations - we work with Azure, Sagemaker, Pandas, Kafka, Ray.
  • Our Support is excellent – we have a quick response time and are willing to walk through your use case with you.

Cons

  • We are working on dashboards – they are currently in beta so they are not polished yet but they will function as intended.
  • There are grouping limitations – you must define your segment at ingest time.
  • We charge per model – like other ML monitoring platforms, our costs grow linearly with your number of models.
  • Advanced capabilities require writing code – limited options in User Interface
  • Excessive overhead at extreme scale -- as much as 5 percent compute time for 10 million+ queries per second
  • Relatively new product -- less entrenched than the major players of the Enterprise space
  • Very limited ability to operate offline -- all processing occurs in the Cloud

Who Is WhyLabs Best For?

Best For

  • Data scientists and ML engineers — Easy-to-use ingestion and monitoring are sufficient for answering most day-to-day questions about model health
  • Small and growing ML teams — Free starter plan includes essential features and an affordable expert plan
  • Organizations prioritizing data privacy — Agents are built to analyze data in-place, avoiding unnecessary duplication
  • Multi-platform ML deployments — Supports a wide variety of integrations within both Cloud and Open Source environments
  • LLM observability needs — Detects toxicity, hallucinations, and jailbreaking of responses based on prompt

Not Suitable For

  • Teams needing polished dashboards immediately — While the beta version has very basic dashboards; they are very unpolished. Consider Arize for a more mature dashboard option
  • Single-model low-volume users — Less cost-effective than using a per-model pricing strategy; use free/open source alternatives whenever possible
  • Enterprises needing extensive explainability — While WhyLabs does provide some level of explainability similar to that of Fiddler; it focuses primarily on model health monitoring and not on providing the same level of detail as other products which specialize in XAI.

Are There Usage Limits or Geographic Restrictions for WhyLabs?

Pricing Model
Per month per model monitored
Free Tier Limits
Starter plan for individuals
Compute Overhead
<1% typical, up to 5% at 10M+ QPS
Data Movement
Privacy-preserving, no data duplication
Compliance Certifications
SOC 2 Type II
Integration Time
Less than 1 hour typical setup

Is WhyLabs Secure and Compliant?

SOC 2 Type IIEnterprise-grade compliance independently audited
Privacy-Preserving AgentsPurpose-built agents analyze raw data without moving or duplicating it
RBAC & SAML SSORole-based access control and SAML SSO for enterprise
API ControlsGranular API access management
Cloud Agnostic SecurityAWS-grade security, works across platforms including Azure
Data in Transit/At RestTLS encryption in transit, profiling ensures data stays secure

What Customer Support Options Does WhyLabs Offer?

Channels
support@whylabs.ai (pre-discontinuation)join.slack.whylabs.ai for community supportwhylabs.ai/docs and GitHub repositories
Hours
Business hours (pre-discontinuation)
Response Time
Community support via Slack; no guaranteed SLA post-discontinuation
Satisfaction
Not available (company discontinued)
Specialized
Slack community for ML engineers and data scientists
Business Tier
Not available (operations discontinued)
Support Limitations
•Operations discontinued following Apple acquisition - no active support
•Community-only support available pre-discontinuation
•No phone or live chat support
•Enterprise support details not publicly documented

What APIs and Integrations Does WhyLabs Support?

API Type
REST API via WhyLabs Observatory platform (discontinued)
Authentication
API keys and OpenTelemetry standards
Webhooks
Actionable alerts for data quality issues and model performance
SDKs
Open-source whylogs (Python), langkit for LLMs; GitHub: github.com/whylabs
Documentation
Comprehensive docs at whylabs.ai/docs (archived); OpenTelemetry integration guides
Sandbox
Freemium SaaS platform with open-source self-hosted option
SLA
Not publicly documented; enterprise custom terms (discontinued)
Rate Limits
Privacy-preserving architecture monitored 100% of data
Use Cases
Data drift detection, model degradation monitoring, LLM observability, production ML pipelines

What Are Common Questions About WhyLabs?

WhyLabs ceased operations after being acquired by Apple. As such, the AI Observability Platform is no longer being maintained or supported.

WhyLabs was an AI observability tool that monitored machine learning models (MLMs), large language models (LLMs), and data pipelines for data drift, model degradation, and quality issues. In addition to being designed to provide privacy preserving architecture for the regulated industry.

Yes, while the WhyLabs product itself is no longer available; the whylogs (the data logging standard) and langkit (LLM observability) were made available under the MIT license on GitHub at https://github.com/whylabs. Both of these pieces can still be used individually.

Data-centric monitoring, feature drift detection, privacy-preserving telemetry, Open Telemetry Integration and real-time alerts were among the key features of the product. In addition to this, WhyLabs addressed the entire AI lifecycle of data through LLMs.

WhyLabs targeted companies in the Healthcare, FinTech, Insurance sectors that had between 200 and 5000 employees and annual revenue greater than $20M. One notable example of a case study is Airspace (aviation/drone technology) and its use of WhyLabs to ensure AI reliability.

Subscription-based SaaS model, with a freemium model: users can download and use the open source tools for free, but must purchase the enterprise platform through the AWS/Azure marketplaces. Pricing will depend on who you speak to (i.e., sales contact) as there are no public pricing tiers available.

A data-layer approach to monitoring data, a privacy preserving architecture for regulated industries and an open-source foundation (whylogs). Proactive vs. reactive model monitoring.

There are currently no active support options available after discontinuation of service. Migrate to alternative platforms or continue using the open-source whylogs and/or langkit. Community support will be available on GitHub.

Is WhyLabs Worth It?

WhyLabs was first to market with AI Observability using unique data-centric monitoring and a privacy preserving architecture to provide effective enterprise solutions for regulated industries. Due to the recent acquisition by Apple, WhyLabs has discontinued operations and its commercial offerings are no longer available. Open-source contributions (whylogs, langkit) are still viable as self-hosted solutions for organizations that require additional ML Observability.

Recommended For

  • For teams looking to implement open-source ML observability (use whylogs).
  • For organizations researching previous approaches to historical AI observability.
  • For ML engineers who used WhyLabs services and want alternatives on GitHub.

!
Use With Caution

  • Currently running production environments - the WhyLabs platform is no longer supported.
  • For enterprises that need support and SLA’s for their commercial AI Observability needs.
  • For teams that require support and maintenance from their vendors.

Not Recommended For

  • For new production deployments that require commercial AI Observability.
  • For organizations that need guarantees of support and updates.
  • Planning budgets - there is currently no active SaaS offering for WhyLabs services.
Expert's Conclusion

WhyLabs pioneered important concepts in AI Observability and is no longer commercially available; use only the open-source components for non-critical self-hosted needs.

Best For
For teams looking to implement open-source ML observability (use whylogs).For organizations researching previous approaches to historical AI observability.For ML engineers who used WhyLabs services and want alternatives on GitHub.

What do expert reviews and research say about WhyLabs?

Key Findings

WhyLabs created the AI Observability category with its data-centric monitoring and privacy-preserving architecture to target regulated industries. Raised $14 million from prominent investors such as Bezos Expeditions and Andrew Ng's AI Fund. After the Apple acquisition, WhyLabs discontinued operations, however the open-source whylogs and/or langkit are actively being maintained on GitHub.

Data Quality

Good - detailed information from CB Insights, company announcements, investor pages, and technical documentation. Limited primary sources post-discontinuation; no active pricing/support details.

Risk Factors

!
Company discontinued operations (there is no longer a commercial platform available).
!
No active support or maintenance is available for the SaaS product.
!
There are few public case studies of the company (the Airspace case study is the only one I could find.)
!
The company does not make its pricing or service-level agreements (SLAs) publicly known.
Last updated: January 2026

What Additional Information Is Available for WhyLabs?

Founder Story

WhyLabs was founded in 2019 by a group of people who worked at the Allen Institute for Artificial Intelligence and previously at Amazon Machine Learning and Cloudflare. They are focused on closing the post-deployment AI visibility gap from Seattle, WA.

Funding History

WhyLabs has raised $14 million in funding overall. It received a $4 million seed round in 2020 and a $10 million Series A in 2021, both rounds were led by Defy Partners and AI Fund, respectively. WhyLabs has also received backing from Bezos Expeditions and Madrona Venture Group. The post-money valuation for the company is around $37 million.

Open Source Contributions

whylogs: an open-standard for data profiling/logging. langkit: an LLM observability toolkit. Both are hosted on GitHub (github.com/whylabs) and continue to have an active user base after discontinuation of the company’s operations.

Community

WhyLabs maintains a Slack community called “join.slack.whylabs.ai.” Users can contribute to the company’s GitHub repositories. The company also uses the Twitter account “@whylabs” for posting updates (which it did before it ceased operations.)

Acquired by Apple

WhyLabs’ operations ceased after the company was acquired by Apple. Apple will be integrating WhyLabs’ technology innovation into their own artificial intelligence and machine learning initiatives. There are no further details about how this will occur specifically.

Industry Recognition

WhyLabs made the top 50 generative AI startup list by CB Insights and the top 100 AI companies. Investors such as Andrew Ng and Bezos Expeditions have validated WhyLabs.

What Are the Best Alternatives to WhyLabs?

  • •
    Fiddler AI: AI Observability with monitoring, explainable AI and analytics for performance of machine learning and large language models. WhyLabs has a strong enterprise focus including government and financial services. WhyLabs provides additional features related to governance that are not provided by WhyLabs. (fiddler.ai)
  • •
    Arthur AI: Enterprise MLOps Platform providing a full suite of model monitoring, large language model evaluation and AI firewalls. Fiddler covers all aspects of deploying, optimizing and meeting regulatory requirements for ML. Fiddler provides more advanced enterprise functionality compared to WhyLabs’ data-focused functionality. Fiddler is best suited for large enterprises with complex ML stacks. (arthur.ai)
  • •
    Mona Labs: Provides complete visibility for GPT applications and GenAI and ML models detecting anomalies. Has a strong focus in e-commerce and real-estate. Provides similar observability scope to WhyLabs but is being maintained and updated actively. Best suited for GenAI-heavy production environments. (monalabs.io)
  • •
    LatticeFlow: LatticeFlow is a platform for enterprise level AI that has built-in capability to assess AI system performance and compliance to regulatory standards. It supports data preparation for machine learning models, continuous development and delivery of AI systems, and provides strong support for European regulatory requirements as it is based out of Zurich, Switzerland. The scope of LatticeFlow is much broader than WhyLabs; where WhyLabs is focused on providing real-time monitoring of AI systems, LatticeFlow has a broader view that includes compliance and validation of AI systems throughout their entire lifecycle. Therefore, organizations that are looking to implement an enterprise-wide AI solution that has strong compliance features would be best served by implementing LatticeFlow.
  • •
    Datadog AI Observability: Datadog is an enterprise-level software platform that offers comprehensive insights into all aspects of an organization's IT environment and operations. In addition to its ability to provide insights into the overall health of an organization's technology environment, Datadog also offers advanced monitoring and analytics tools specifically designed to monitor the performance of machine learning systems. As such, organizations that have a high degree of maturity and that are utilizing Datadog to monitor and analyze their IT environment would likely find it easier to integrate WhyLabs into their existing technology stack than organizations that do not currently utilize Datadog. Organizations should consider utilizing Datadog when they are looking for a highly scalable and mature observability platform that can provide a broad range of insights into both traditional IT and machine learning systems.

What Are WhyLabs's Evaluation Metrics?

Unlimited
Profile Count
Data quality, drift, performance
Anomaly Types
Accuracy, F1, MSE, etc.
Performance Metrics

What Testing Capabilities Does WhyLabs Offer?

Data Drift Detection

This capability monitors how input or output distributions have changed

Performance Monitoring

This capability tracks classification, regression, ranking metric values

Anomaly Detection

This capability identifies changes in data quality and/or behavior

Segment Analysis

This capability analyzes metrics across data segments

Explainability

This capability visualizes feature importance

How Does WhyLabs's Benchmark Support Compare?

BenchmarkCategorySupported
Custom BaselinesDrift DetectionYes
Performance MetricsModel EvalYes
whylogs ProfilesData QualityYes
Segment MetricsBias AnalysisYes

What Model Compatibility Does WhyLabs Support?

All LLMsClassificationRegressionRankingCustom Models

How Does WhyLabs Ensure Safety Through Testing?

Prompt Injection

This capability detects potential attacks

Toxicity Monitoring

This capability flags potentially toxic prompts/responses

Context Reliability

This capability checks if responses were relevant

Data Quality

This capability monitors schema changes/corruption

Bias Detection

This capability allows you to segment your data to ensure that there is fairness in the way it is treated

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