WhyLabs
Paid
0
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WhyLabs

AI Infrastructure

Enable MLOps with cloud-agnostic model monitoring via the WhyLabs AI Observability Platform.

Model Monitoring with the WhyLabs AI Observability Platform

WhyLabs is a cutting-edge platform designed to enable MLOps with a focus on model monitoring and data monitoring. The platform is cloud-agnostic, ensuring flexibility and scalability for businesses of all sizes. With WhyLabs, users can monitor both structured and unstructured data, as well as a wide range of ML models. The platform also offers the open standard for data logging, known as whylogs, which generates privacy-preserving dataset summaries. Additionally, LangKit is available to monitor and safeguard LLMs, providing essential guardrails, evaluations, and observability.

Key Features:

  • WhyLabs Observatory: Monitor structured or unstructured data and all ML models.
  • whylogs: An open standard for data logging that generates privacy-preserving dataset summaries.
  • LangKit: Safeguard and monitor LLMs with essential guardrails and evaluations.
  • AI Observability: Monitor AI systems in various industries, including financial services, logistics, retail, and healthcare.

Ideal Use Case:

Businesses and organizations looking to ensure the reliability and efficiency of their AI models would benefit immensely from WhyLabs. The platform is especially useful for those who want to detect and mitigate risks in their AI applications, continuously monitor data quality, and identify model drifts.

Why use WhyLabs:

  • Data Security: Integrate without moving or duplicating raw data, ensuring maximum privacy and security.
  • Comprehensive Monitoring: Monitor predictive models, generative models, data pipelines, and feature stores.
  • Enterprise-Grade Features: Offers features like RBAC, SAML SSO, API controls, and advanced trigger configurations.
  • Powerful Monitoring Algorithms: Provides intelligent baselines and seasonal monitors.

tl;dr:

WhyLabs offers a comprehensive AI observability platform that enables MLOps with model and data monitoring. With features like whylogs and LangKit, businesses can ensure the reliability and efficiency of their AI models.

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