WhyLabs AI Observatory
The WhyLabs AI Observability Platform is a cloud-agnostic solution that enables MLOps by providing model monitoring and data monitoring capabilities. It supports monitoring of any type of data at any scale. The platform helps detect data and machine learning (ML) issues faster, delivers continuous improvements, and prevents costly incidents.
Description
how to use:
To use the WhyLabs AI Observability Platform, you need to integrate the purpose-built agents with your existing data pipelines and multi-cloud architectures. The platform provides secure integration with built-in agents that analyze raw data without moving or duplicating it, ensuring data privacy and security. You can then continuously monitor your predictive models, generative models, data pipelines, and feature stores using the integrated agents. The platform also supports monitoring of structured or unstructured data by running whylogs on your data and uploading the logs to the platform.
Core freatures:
Model and data health monitoringContinuous monitoring for model input and output driftIdentification of training-serving skewImprovement of AI performance by identifying the best model candidate and reliable featuresTraceability of cohorts that contribute to model performance and introduce biasProactive resolution of data quality issues in feature pipelines and feature storesLLM (Language and Learning Models) security for self-hosted and proprietary LLM APIsInline actions to protect against prompts with malicious intent and abuse riskProtection against OWASP Top 10 vulnerabilities, such as prompt injections and data leakageContinuous evaluation of LLM prompts and responses to ensure a positive user experienceEnterprise-grade features, including RBAC, SAML SSO, API controls, and advanced trigger and notification configurationsSecurity compliance (SOC 2 Type 2)Hybrid SaaS deployment model for highly confidential modelsRoot cause analysis tools for issue investigationPowerful monitoring algorithms for intelligent baseline and seasonal monitorsSeamless integration with existing pipelines and tools
Use case:
Financial Services: Safeguard financial services businesses from the risks of AI bias and opaqueness
Logistics & Manufacturing: Ensure AI continuously delivers an advantage to logistics and manufacturing businesses
Retail & E-commerce: Optimize retail business decisions and ensure accurate and reliable models
Healthcare: Monitor AI systems used in healthcare to ensure reliability, compliance, and patient safety
FAQ list:
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