Everything you need to trust your AI
One platform for monitoring, explainability, fairness, and governance across traditional ML and large language models — now with one-step model connections over MCP.
The Governance Layer for the Agent Ecosystem
The WhiteBox MCP server turns isolated AI components into a unified, compliant ecosystem. Wire up your assistants, agent frameworks, and serving environments over the Model Context Protocol — and WhiteBox instantly becomes your system of record. Generate audit artifacts and enforce policies across all agents, all with zero glue code.
{
"mcpServers": {
"whiteboxxai": {
"command": "npx",
"args": ["-y", "@whiteboxxai/mcp-server"],
"env": { "WHITEBOX_API_KEY": "wbx_..." }
}
}
}Rolling out now — MCP support ships alongside the existing Python SDK and REST API, which remain fully supported.
The System of Record
Point the MCP server at WhiteBox once. Models, agents, and assistants register and log through the same standard tools — becoming the default governance layer for your entire agent ecosystem.
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.
Verifiable Observability
Every call through the server is logged, profiled, and verified — generating defensible trace logs, drift tests, and forensic compliance artifacts 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.
MCP Governance LayerSystem of Record
The system of record for your agent ecosystem. Connect models, agents, and assistants over the Model Context Protocol to automatically generate compliance artifacts with zero glue code.
Real-Time Monitoring & Drift
Continuous performance tracking with Kolmogorov-Smirnov, PSI, Chi-squared, and ADWIN tests to catch data and concept drift before it costs you.
Explainability (XAI)
Defensible evidence for every model output. We translate complex ML telemetry—from tabular SHAP/LIME to LLM counterfactuals and agent tracing—into plain-language PDF reports for auditors.
Bias & Fairness Auditing
Demographic parity, equal opportunity, equalized odds, and disparate impact — with automated audits and mitigation recommendations compiled into compliance reports.
LLM & RAG Audit TrailsLLM-Ready
Automated claim-level verification and RAG faithfulness scoring. Instantly report on PII leakage, toxicity, and jailbreak attempts with end-to-end trace logs for every agent and tool call.
Intelligent Alerting
Threshold and anomaly alerts routed to Slack, email, webhooks, SMS, and PagerDuty — with correlation and fatigue reduction built in.
Compliance Reporting
Continuous, auto-generated evidence mapped directly to ISO 42001, GDPR, CCPA, and EU AI Act obligations (including transparency and AI-generated content disclosures).
Unified Trust ScoreNew
A single 0–100 executive score per model, aggregating bias audit results, drift severity, and explainability coverage — with a full component breakdown, portfolio rollup, historical trend, and configurable weighting, included in every PDF evidence export.
AI Risk RegisterNew
Catalog, score by likelihood × impact, and track mitigation status for risk across your entire model portfolio — with a portfolio heat map, full audit trail, and entries auto-drafted from failed bias audits and high-severity drift.
RACI DashboardNew
Assign Responsible, Accountable, Consulted, and Informed roles per governance review request, drawn from your review board's real membership — with a matrix view across every board.
State-Level ComplianceNew
Automated Impact Assessments for the Colorado AI Act and Transparency Reports for the Illinois AI Safety Measures Act.
Policy-as-Code & GitOpsNew
Define escalation rules and governance policies directly in whitebox.yaml. Full GitOps control natively via CI/CD, keeping it easy for compliance AND engineering to use.
Lightweight SDK
Drop-in Python SDK with integrations for scikit-learn, PyTorch, TensorFlow, Hugging Face, LangChain, and XGBoost — minimal overhead.
GitHub Integration
Link production behavior back to the exact commit. Auto-register model versions and track changes across your Git history.
SDK integrations for your ML stack
Fits into the tools you already use
Connect version control, alerting, and governance tooling — no rip-and-replace required.
Link production behavior back to the exact commit and auto-register model versions from your repos.
Route drift, bias, and performance alerts straight to the channels your team already watches.
Escalate a drift, bias, or control-failure alert into PagerDuty the moment it fires, with correlation and fatigue reduction built in.
Send alert notifications and scheduled compliance reports directly to stakeholder inboxes.
Pipe any alert or event into your own systems — ticketing, ChatOps, or internal automations.
Send an SMS alert to whoever owns the response when a finding can't wait for email or Slack.
Sync bias/fairness reports, drift logs, and audit trails directly into your OneTrust GRC workflows.
Feed AI governance evidence — bias audits, drift logs, and model documentation — into your Vanta compliance automation.
Push continuous AI monitoring evidence into Drata to keep your controls audit-ready without manual collection.
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.
For Regulated Enterprises, AI Governance is No Longer Optional.
As AI moves from experiments to production systems making consequential decisions, teams cobbling together custom evals and spreadsheets simply won't cut it. For regulated banks and insurers, audit trails, drift detection, and compliance artifacts are essential infrastructure.
WhiteBox leans into what can be verified. Centralize your governance with our flagship AI Risk Register—something traditional GRC tools lack. Generate defensible incident forensics and compliance reports so when the board asks about AI risk, you have real evidence, not just a slide deck.
See what your AI has been hiding.
Request an enterprise demo and walk through real drift detection, explainability, and governance workflows.