Key Features of WhyLabs AI Observability Platform
- Model and data health monitoring
- Continuous tracking of model input and output drift
- Detection of training-serving skew
- Enhancement of AI performance through optimal model selection and feature identification
- Traceability of cohorts impacting model performance and bias introduction
- Preventive measures for data quality issues in feature pipelines and stores
- LLM security for self-hosted and proprietary LLM APIs
- Inline actions to counter malicious prompts and abuse risks
- Security measures against OWASP Top 10 vulnerabilities
- Continuous evaluation of LLM prompts for enhanced user experience
- Enterprise-grade features like RBAC, SAML SSO, and advanced trigger configurations
- Security compliance with SOC 2 Type 2 standards
- Hybrid SaaS deployment model for sensitive models
- Tools for root cause analysis and issue resolution
- Intelligent monitoring algorithms for baseline and seasonal analysis
- Seamless integration with existing tools and pipelines
Applications of WhyLabs AI Observability Platform
- Financial Services: Mitigate AI bias and enhance transparency in financial operations
- Logistics & Manufacturing: Drive competitive advantage through continuous AI optimization
- Retail & E-commerce: Improve decision-making and model accuracy in retail settings
- Healthcare: Ensure reliability, compliance, and patient safety in healthcare AI systems