WhyLabs AI Observability Platform

WhyLabs AI Control Center (WhyLabs Platform) is an open-source-friendly AI observability and LLM security platform designed to help organizations observe, secure, and optimize AI-powered applications across data, model, and deployment layers. It provides end-to-end visibility into data quality, model health, security guardrails, and governance for traditional ML models, large language models (LLMs), and multimodal AI systems. The platform emphasizes privacy-preserving telemetry, configurable guardrails, real-time monitoring, and rapid remediation to prevent harmful or degraded AI behavior in production.

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How it works

1. Install and connect data sources, model endpoints, and pipelines to collect telemetry without exposing raw data.
2. Instrument guardrails, evaluations, and observability rules using LangKit and whylogs to monitor prompts, responses, and data quality.
3. Monitor model health, security risks (prompt injections, data leakage, toxicity), drift, and performance across all deployed AI applications.
4. Receive real-time alerts, automated remediation, and dashboards to coordinate between ML, SRE, and Security teams.

Core Capabilities

• Observe: 100% inference telemetry with data-centric visibility; detect drift, data quality issues, and model degradation across all modalities.
• Secure: detect and block security risks in real-time; enforce guardrails for prompts, responses, and data usage.
• Optimize: analyze prompts and responses to improve model behavior and calibrate guardrails; support data-centric MLOps workflows.
• Log and Privacy: local telemetry capture with privacy-preserving data handling; no raw data movement required to third parties.
• Collaboration: governance and observability workflows that align data scientists, SREs, and security teams.

Use Cases by Industry

• Financial Services: safeguard AI-driven decisions, reduce bias, and improve transparency.
• Logistics & Manufacturing: ensure AI-assisted operations deliver reliable, compliant outcomes.
• Retail & E-commerce: monitor model accuracy and decision quality for pricing, recommendations, and risk.
• Healthcare: ensure reliability, regulatory compliance, and patient safety in AI-enabled workflows.

Product Tiers and Open Source Alignment

• Open source components (e.g., whylogs) for data logging and privacy-preserving telemetry.
• LangKit: framework to implement guardrails, evaluations, and observability for LLMs.
• OpenLLMTelemetry: real-time tracing and monitoring for LLM-based systems via OpenTelemetry integration.
• SOC 2 Type 2-compliant privacy-friendly deployment option for regulated industries.

How WhyLabs Helps AI Teams

• Guardrails: block harmful interactions (prompt injections, jailbreak attempts, PII leakage) in real-time.
• Drift & Quality: detect drift, monitor data quality, and identify failing cohorts to improve model health equity.
• Remediation: automate remediation actions to address threats and performance issues.
• Visibility Across Modalities: secure and observe text, code, images, documents, voice, and video.
• Collaboration: configure roles and dashboards to accelerate issue resolution across teams.

Safety and Legal Considerations

• Emphasizes privacy-preserving telemetry and does not require raw data movement to third-party services. Guardrails help prevent misuse and protect user privacy.

Core Features

• Comprehensive AI observability across data, models, and deployments
• Real-time security guardrails for prompts, responses, and data handling
• Data-centric MLOps tooling for prompt and model evaluation
• LangKit for customizable guardrails and evaluations
• whylogs-based privacy-preserving data logging and profiling
• OpenTelemetry integration for end-to-end tracing of LLM-based systems
• Privacy-preserving telemetry that avoids uploading raw data
• SOC 2 Type 2 compliant deployment options for regulated industries
• Multi-domain industry support (Finance, Healthcare, Retail, Logistics, etc.)
• Scalable monitoring of LLMs, ML models, and multimodal AI
• Collaboration-ready dashboards for ML, SRE, and security teams

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How to Use WhyLabs AI Control Center

1. Connect data sources, model endpoints, and pipelines to start collecting telemetry.
2. Configure LangKit guardrails and evaluation rules for your prompts and model outputs.
3. Monitor dashboards to detect drift, data quality issues, and security risks in real time.
4. Respond with automated remediation and governance workflows to maintain safe and reliable AI applications.

Safety and Compliance

• Real-time risk detection and blocking of harmful interactions.
• Privacy-forward data collection with local telemetry and non-retentive data handling.
• Governance capabilities to support compliance across industries.

WhyLabs Value Proposition

• The leading platform for observe, secure, and optimize AI applications at scale.
• Enables data-centric, auditable, and privacy-preserving AI operations across multiple models and modalities.
• Bridges the gap between AI development and reliable production operations with guardrails and observability.