WhyLabs provides real-time monitoring and management tools for machine learning and generative AI applications, enabling teams to detect and mitigate security risks, model drift, and performance issues. By automating threat remediation and ensuring data privacy, WhyLabs reduces manual operations by over 80% and accelerates incident resolution by 20 times.
Funding
$14M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
AFDVFounders
Product
Problem
Machine learning and generative AI applications are susceptible to security risks, model drift, and performance degradation, which can negatively impact application reliability and user experience. Detecting and mitigating these issues often requires significant manual effort from ML, SRE, and security teams. Current monitoring solutions may lack the necessary real-time capabilities and privacy-preserving features required for highly regulated industries.
Solution
WhyLabs provides a real-time AI observability platform that enables teams to monitor, secure, and optimize machine learning and generative AI applications. The platform offers comprehensive monitoring across multiple dimensions of security and quality, including the ability to observe, flag, and block security risks in real-time. It automates the remediation of security threats, model performance degradation, and data quality issues, reducing manual operations and accelerating incident resolution. WhyLabs integrates seamlessly with existing AI and data ecosystems, supporting various cloud providers and multi-cloud environments. The platform's privacy-preserving techniques ensure that sensitive data remains protected, making it suitable for use in highly regulated industries such as healthcare and financial services.
Target Audience
The primary target audience includes ML engineers, SRE teams, security teams, and data scientists responsible for building, deploying, and maintaining machine learning and generative AI applications across various industries.
Features
- Real-time monitoring of AI application health, including data quality and model performance
- Automated detection and remediation of security threats, model drift, and data quality issues
- Customizable security guardrails to block harmful interactions, prompt injections, and data leakage
- Support for monitoring and evaluating large language models (LLMs) and generative AI across multiple modalities (text, images, video, etc.)
- Integration with 50+ AI and data ecosystem tools, including cloud providers and feature stores
- Privacy-preserving deployment approved for highly regulated industries (Healthcare and FSI)
- Custom dashboards for visualizing model health and reducing time to resolution of AI issues
- Ability to bring your own models and red teaming scenarios for customized security configurations