Harness the power of

with precision and control

AI powers your most impactful applications. WhyLabs gives you the tools to ensure these applications are secure, reliable, and performant.

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Thousands of users love and trust WhyLabs:

Observe, Secure, and Optimize

your AI applications

Control every aspect of your AI application health
Observe, flag, and block security risks in real-time
Get notified about drift and performance degradations across all predictive models
Automate remediation of security threats, model performance degradation, and data quality issues
Enable seamless collaboration across ML teams, SRE teams, and security teams
The only SaaS privacy-preserving deployment approved for highly regulated industries (Healthcare and FSI)

Large Language Models

Monitor, evaluate, and guardrail across multiple dimensions of security and quality. Safeguard proprietary LLM APIs and self-hosted LLMs.

Generative AI

Go beyond text-to-text. Secure and observe any modality - images, documents voice, or video.

Predictive AI

Enable MLOps best practices for traditional AI models with observability and monitoring for any model type.

The leader in LLMOps and MLSecOps tools

High Performer Americas Winter 2024 Badge

Interested to know what leading AI teams are saying about WhyLabs? Click here.

Take Control Of Your AI Applications

Understand every aspect of model health, from data quality to performance.

Stop harmful model interactions in real time, before they impact the end user experience.

Rely on the latest methods to flag and block harmful interactions in real-time.

Fine tune and continuously improve AI applications using the insights and datasets curated

Best-in-class teams rely on WhyLabs to control their AI applications

Join the responsible
AI Builders

installs

Make guardrails
decisions with

300

avg. latency

Protect your
AI experiences with

93%

avg. accuracy

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Secure and Protect

Block harmful interactions: prompt injections, jailbreak attempts, and data leakage.

Protect the customer experience by blocking toxic responses and rerouting unapproved topics.

Prevent hallucinations and over-reliance: flag responses that are not supported by the RAG context or consistency checks.

Prevent misuse of the AI application by blocking and flagging unapproved topics, PII leakage, and high cost queries.

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Observe Any Application at Scale

Continuously monitor model health across a wide range of statistical and derived metrics. Detect and resolve model drift.

Improve model performance by identifying the best model candidate and the most reliable features.

Trace which cohorts contribute to model performance and introduce bias.

Observe 100% of the inferences without sampling and duplicating the inference data.

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Optimize and Customize

Enable continuous application improvement using insights from prompts and responses captured and annotated by the guardrails.

Onboard quickly with intelligent observability configurations, allowing for zero-config onboarding and full customization.

Configure the security guardrail to your unique needs: bring your own models, your red teaming scenarios, and your examples.

Empower your team with custom dashboards that reduce time to resolution of AI issues by 10x.

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Integrate Seamlessly

Use WhyLabs with any cloud provider and in multi-cloud environments.

Switch on observability in your entire AI and data ecosystem with 50+ integrations.

Enable guardrails and tracing for any GenAI proprietary API or self-hosted model.

Bring data-centric approach to your AI organization by validating data quality across your pipelines and feature stores.

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Protect Privacy

WhyLabs never moves or duplicates your model raw data. Our proprietary technique capture all necessary telemetry locally.

WhyLabs is SOC 2 Type 2 compliant and approved by security teams at Healthcare companies and Banks.

WhyLabs LLM guardrail and evaluation techniques do not use third-party LLMs, and never require raw prompt and response data to lease the customer VPC.

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What leading AI teams are saying about WhyLabs

“I think tools like this could really help standardize around what types of things you're alerting on, and how you're defining those rules. And how you're visualizing it. Which would not only be useful for data scientists, but I think it would also be useful for other stakeholders. For PMs and POs, and engineers that are actively managing these products, after they are live.”

Senior Data Scientist

Getty Images

“We chose WhyLabs for several reasons. First, they provide all the core model monitoring functionalities that we're looking for including a straightforward presentation of results, outlier detection, histograms, data drift monitoring, and missing feature values. [Second,] they have strong data privacy due to their aggregation of data before consumption and very fast ingestion.”

ML Platform Program Manager

Fortune 500 Fintech

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“At Airspace, we use AI to minimize risk across the supply chain for the world's most critical shipments. WhyLabs has been instrumental in driving the scalability of our AI operations. The platform offers easy onboarding, data privacy-friendly integration, and a command-center view that allows us to quickly identify and treat problems before they impact the user experience. The downstream impact of enabling observability is that we are able to continuously expand on our differentiating technology by leveraging machine learning for more use cases”

Ryan Rusnak

Co-founder and CTO, Airspace

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“We chose WhyLabs as an observability capability for our ML Platform because of the ease of integration and rich capabilities that enable us to meet Model Health Equity Governance guidelines and minimize time-to-insight across model operation tasks.”

Engineering Director

Major Healthcare Provider

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"If we're waking up engineers at 3 am, we need to be confident that we're not reporting on false positives."

IT Operations Manager

Fortune 500 Retail

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"WhyLabs provides a safety net for us that we didn’t have before. As a result, we are able to iterate on new experiments and prompts faster and ship new AI features quickly. We can do so with high confidence, knowing we have quantitative metrics to back up our decisions."

CEO

Yoodli

Read the case study

“We love how easy it was to integrate whylogs with our custom infrastructure. whylogs allows our data scientists to get insights about their datasets and monitor the models that they deploy.”

Nobuyuki Kuromatsu

Platform Engineer (MLOps), AI Platform Team
Yahoo Japan Corporation

“At Stitch Fix we have hundreds of workflows that connect to production microservices all driven and deployed by Algorithms team members. Observability is essential to ensure that these services are robust and deliver consistent customer experiences. We are excited to collaborate with WhyLabs on building an open source standard for data logging that helps us streamline observability across our data and AI pipelines, be it offline or online.”

Stefan Krawczyk

Manager of Model Lifecycle, Stitch Fix

“ML engineers need better tools to ensure high-quality data through all stages of an ML project's lifecycle. AI Fund is excited to support WhyLabs, whose open source logging library and AI observability platform makes it easy for developers to maintain real time logs and monitor ML deployments.”

Andrew Ng

Managing General Partner, AI Fund

“We need tools that enable our machine learning team to ensure AI models help inform seamless experiences for customers and achieve business objectives when running at a very high scale. WhyLabs' monitoring solution takes a practical and elegant approach to monitoring the input and output data, statistics and behavior of models in flight at scale, filling the gap between software and machine learning model operations.”

Olly Downs

VP of Martech, Data and Machine Learning, Zulily

“We are business-to-business, and a lot of our customers don't know anything about ML. So they might make what seems to them quite as obvious and harmless changes, that has terrible impact internally. Having something like this would have prevented a lot of problems.”

Machine Learning Engineer

Sift Science

Senior Data Scientist

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ML Platform Program Manager

Fortune 500 Fintech

Read the case study

Ryan Rusnak

Co-founder and CTO, Airspace

Read the case study

Engineering Director

Major Healthcare Provider

Read the case study

"If we're waking up engineers at 3 am, we need to be confident that we're not reporting on false positives."

IT Operations Manager

Fortune 500 Retail

Read the case study

CEO

Yoodli

Read the case study

“We love how easy it was to integrate whylogs with our custom infrastructure. whylogs allows our data scientists to get insights about their datasets and monitor the models that they deploy.”

Nobuyuki Kuromatsu

Platform Engineer (MLOps), AI Platform Team
Yahoo Japan Corporation

Stefan Krawczyk

Manager of Model Lifecycle, Stitch Fix

Andrew Ng

Managing General Partner, AI Fund

Olly Downs

VP of Martech, Data and Machine Learning, Zulily

Machine Learning Engineer

Sift Science

Senior Data Scientist

Getty Images

Run AI with Certainty

Book a demo

Harness the power of

with precision and control

Observe, Secure, and Optimize

your AI applications

Large Language Models

Generative AI

Predictive AI

The leader in LLMOps and MLSecOps tools

Take Control Of Your AI Applications

Secure and Protect

Observe Any Application at Scale

Optimize and Customize

Integrate Seamlessly

Protect Privacy

What leading AI teams are saying about WhyLabs

Run AI with Certainty

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