WhyLabs AI Control Center

Observe, Secure, and Optimize your AI applications.

Freemium

Description

WhyLabs AI Control Center provides a robust platform designed to ensure that artificial intelligence applications operate securely, reliably, and at peak performance. It empowers organizations to manage the entire lifecycle of their AI models by offering advanced tools for observability, enabling teams to understand model health, detect data quality issues, and monitor for drift and performance degradation across all predictive and generative models. The platform focuses on providing real-time insights and actionable alerts to maintain AI integrity.

Supporting a wide array of AI systems, including Large Language Models (LLMs), Generative AI across various modalities (text, images, documents, voice, video), and traditional predictive AI, WhyLabs facilitates the implementation of MLOps best practices. It allows users to flag and block security risks such as prompt injections and data leakage, automate remediation processes, and ensure compliance. A key aspect of WhyLabs is its privacy-preserving architecture, which processes data locally using statistical profiles, making it suitable for deployment in highly regulated industries like healthcare and financial services without moving or duplicating raw data.

Key Features

Real-time AI Security: Observe, flag, and block security risks like prompt injections, jailbreak attempts, and data leakage in real-time, protecting customer experience by managing harmful interactions.
Comprehensive AI Observability: Continuously monitor model health, data quality, drift, and performance degradations across all predictive models, LLMs, and generative AI, without data sampling.
Automated Remediation & Alerting: Automate responses to security threats, model performance degradation, and data quality issues, with notifications for drift and performance issues.
LLM & GenAI Guardrails: Monitor, evaluate, and implement guardrails for Large Language Models and Generative AI across multiple dimensions of security and quality, supporting various modalities like text, images, documents, voice, and video.
Privacy-Preserving Architecture: Utilizes proprietary local telemetry capture via whylogs (open source standard for data logging) ensuring raw data never leaves the customer environment; SOC 2 Type 2 compliant.
Seamless Integration & Customization: Works with any cloud provider and in multi-cloud environments, offers over 50 integrations, and allows full customization of configurations, guardrails, and dashboards.
Actionable Insights for Optimization: Enables continuous application improvement using insights from prompts and responses captured and annotated by guardrails, and helps identify best model candidates.

Use Cases

Securing Large Language Model (LLM) Applications against misuse and threats.
Comprehensive Machine Learning Model Monitoring for performance and drift.
AI Observability for data-driven enterprises across various AI types.
Managing AI Risk and Compliance in Financial Services.
Optimizing AI Performance and Reliability in Retail and E-commerce.
Ensuring AI System Reliability and Patient Safety in Healthcare.
Improving AI Efficiency and Advantage in Logistics and Manufacturing.

Frequently Asked Questions

What data does WhyLabs collect?

None at all. WhyLabs relies on statistical profiles of your data generated by its open-source library, whylogs. Your raw data never leaves your environment as profiles are generated locally.

Can I monitor both data and models?

Yes. WhyLabs allows you to collect metadata and monitor data whether it's in an ML model, a data stream, or a data pipeline, tracking aspects like data drift, model performance, and data quality.

What data types can I monitor?

You can monitor various data types including tabular, text, image, embedding, video, or audio data. It supports both batch and streaming data.

What model types can I monitor?

WhyLabs is model-agnostic. For performance evaluation, it supports output types such as Language/LLM, Classification, Regression, Embeddings, Sequence, Recommendation systems, Bounding box, and Forecast models.

How does WhyLabs monitor 100% of the data, without sampling?

WhyLabs uses statistical profiles generated by whylogs. These profiles are highly efficient and scalable, accurately representing massive data volumes without needing to resort to sampling.