The Era of
Transparent AI
Stop guessing why your models make decisions. Monitor, explain, and govern your production AI — with the evidence to prove it.
- Dozens
- Popular Large Language Models, multi-agentic workflows, and AI/ML frameworks supported
- ISO 42001
- Compliance mapping built-in
- SHAP · LIME
- Explainability engines
WhiteBox XAI is an advanced, enterprise-grade observability and explainability (XAI) platform that demystifies your production AI models. It provides the deep, real-time insights necessary to monitor, understand, and trust your AI and LLM applications, moving beyond performance metrics to reveal why your models make the decisions they do.
WhiteBox XAI is the essential tool for ensuring your AI systems are not only effective but also fair, compliant, and transparent.
Built on standards you already trust
- SHAP
- LIME
- ISO/IEC 42001
- GDPR
- CCPA
- NIST AI RMF
- EU AI Act
AI Risk Officers: Get professional AI bias/fairness reports, drift logs, and audit trails you can hand to an auditor without translating the technical output yourself.
Connect Any Model In Minutes, Not Sprints
The WhiteBoxXAI MCP server turns model onboarding into a single configuration block. Wire up your assistants, agent frameworks, and serving environments over the Model Context Protocol — and start monitoring, explaining, and governing them the moment they connect.
{
"mcpServers": {
"whiteboxxai": {
"command": "npx",
"args": ["-y", "@whiteboxxai/mcp-server"],
"env": { "WHITEBOXXAI_API_KEY": "wbx_..." }
}
}
}Rolling out now — MCP support ships alongside the existing Python SDK and REST API, which remain fully supported.
Connect In One Step
Point the MCP server at WhiteBoxXAI once. Your models, agents, and assistants register themselves — no glue code, no bespoke client per framework.
Standard Tooling
Model Context Protocol is the open standard for connecting AI systems to tools and data. Any MCP-capable client speaks it out of the box.
Observability Built In
Every call through the server is logged, profiled, and explainable — drift tests, token and cost tracking, and SHAP/LIME explanations without extra instrumentation.
Governed By Default
Scoped credentials, full audit trails, and policy enforcement travel with the connection, so agent access stays inside your governance boundary.
Don't Just Deploy AI—Audit AI
An observability and explainability platform that demystifies your production AI models — revealing why they make the decisions they do.
Build Trust
Eliminate the "black box" problem. Provide transparent, understandable explanations to business stakeholders, customers, and regulators.
Mitigate Risk
Proactively detect model decay, data quality issues, and algorithmic bias before they lead to poor business decisions or reputational damage.
Ensure Compliance
Simplify the process of auditing AI systems and demonstrating compliance with internal governance policies and external regulations.
Accelerate Debugging
Radically shorten the time it takes to diagnose and resolve production model issues with detailed root-cause analysis dashboards.
From black box to full transparency
Four steps take you from an unmonitored model to a fully observable, explainable, and governed AI system.
- 1
Connect your model
Drop the lightweight SDK into your serving environment or wire up the REST API. Register models from scikit-learn, PyTorch, TensorFlow, Hugging Face, XGBoost, and LLM providers.
- 2
Monitor in real time
Every prediction is logged and profiled. Statistical tests (KS, PSI, Chi-squared) surface data and concept drift the moment production behavior diverges from your baseline.
- 3
Explain every decision
SHAP and LIME turn opaque outputs into human-readable, feature-level explanations — so stakeholders, customers, and regulators can see exactly why a decision was made.
- 4
Govern & prove compliance
Bias audits, review-board approvals, and a full-text searchable decision archive map to ISO 42001, GDPR, CCPA, and the EU AI Act — audit-ready by design.
Audit-ready, by design
Every model decision, review, and drift event is logged to a full-text searchable archive — evidence you can hand an auditor directly, or feed straight into the GRC platform you already run.
Automated AI management system compliance tracking, evidence collection, and control mapping.
Automated impact assessments and right-to-explanation evidence for every AI-driven decision.
Model-level evidence for automated decision-making disclosures under California law.
Multi-party approval workflows with executive oversight and a searchable decision archive.
Recommended by AI Governance Advisors
“Cyber Ready recommends WhiteBox AI as a valuable solution for organizations seeking to strengthen AI risk management and ISO/IEC 42001 audit readiness by bringing structure, accountability, governance, and evidence into one centralized platform.”
See what your AI has been hiding.
Request an enterprise demo and walk through real drift detection, explainability, and governance workflows.