whylabs.ai Open in urlscan Pro
2606:4700:3033::ac43:9e98  Public Scan

Form analysis
0 forms found in the DOM

Text Content

Product

PLATFORM

WhyLabs AI Control Center

AI Control Center keeps AI applications secure as observability alone becomes
insufficient in the era of Generative AI

Observe



Secure



Optimize



SIGN UPLog in

Open Source

whylogs: The open standard for data logging

Generate privacy-preserving dataset summaries, called whylogs profiles

LangKit

Monitor and safeguard LLMs with LangKit to implement guardrails, evaluations,
and observability

OpenLLMTelemetry

Real-time tracing and monitoring of LLM-based systems using an Open Telemetry
integration
Solutions

SOLUTIONS

Solutions for the data-driven enterprise

A scalable solution for data-driven enterprises in all major verticals

Safeguard LLMs with LangKit

Extract actionable insights about prompts and responses with a data centric
approach to LLMOps

LLM Security



ML Monitoring



AI Observability



INDUSTRIES

Financial Services

Safeguard your financial services business from the risks of AI bias and
opaqueness

Logistics & Manufacturing

Ensure AI is continuously delivering an advantage to your logistics and
manufacturing business

Retail & E-commerce

Optimize Retail business decisions and ensure models are accurate and reliable

Healthcare

Monitoring AI systems used in Healthcare ensures reliability, compliance, and
patient safety.

CUSTOMERS

Case studies



Case study: Yoodli



Case study: Airspace



Case study: Fortune 500 FinTech



Case study: Fortune 500 Retail



Case study: Healthcare Provider


Pricing
Docs

DOCUMENTATION

WhyLabs AI Control Platform



whylogs



LangKit


Resources

COMPANY

About WhyLabs



Blog



Integrations



AWS Marketplace



FAQs



Careers



Press



CONNECT

Events



Join the R2AI Community

Be part of a growing community that comes together and make AI technology robust
and responsible.

Contact us



Book a demo

KNOWLEDGE CENTER

Build vs. Buy: A Definitive Guide



Data Privacy



Learn with WhyLabs



LLMOps White Paper



MLOps and DataOps Glossary



MLOps White Paper



Log inBook a demo



HARNESS THE POWER OF
AI|


WITH PRECISION AND CONTROL

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

Get started for freeBook a demoBook a demo

Start for free right now with the Starter plan

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

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

 * Take Control
 * Secure
 * Observe
 * Optimize
 * Integrate
 * Protect Privacy

Take Control

 * Take Control
 * Secure
 * Observe
 * Optimize
 * Integrate
 * Protect Privacy


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

5,050,456

installs

Make guardrails
decisions with

300

ms

avg. latency

Protect your
AI experiences with

93%

avg. accuracy

Learn More


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.
Learn More



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.
Learn More



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.
Learn More



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.
Learn More



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.
Learn More




WHAT LEADING AI TEAMS ARE SAYING ABOUT WHYLABS

Previous

“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

Read the case study

“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

Read the case study

“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

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

"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

“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

Read the case study

“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

Read the case study

“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

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

"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

“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

Next



RUN AI WITH CERTAINTY

Book a demo



ABOUT

 * Careers
 * Contact Us
 * Privacy Policy
 * Terms of Use


RESOURCES

 * AI Observability
 * ML Monitoring
 * Blog
 * Learn with WhyLabs
 * Glossary
 * Slack Community
 * AWS Partnership
 * MLOps White Paper
 * LLMOps White Paper
 * Build vs. Buy Guide
 * FAQ


WHYLOGS

 * GitHub Repository
 * Documentation


WHYLABS

 * Book a demo
 * Get started for free
 * Events

 * 
 * 
 * 
 * 

Copyright © 2024 WhyLabs, Inc. All Rights Reserved.

 * Privacy policy
 * Terms of use

This site uses cookies for analytics, personalized content and ads. By
continuing to browse this site, you agree to this use. To learn more, you can
review our Privacy Policy.
Got it
Please enable JavaScript to run this website.
loading...