Live Agent Monitoring
Every lending, fraud, and payment decision tracked in real time — not reviewed weeks later in spreadsheets
Governance layer for agents.
Compliance observability for every AI agent in finance — logged, auditable, regulator-ready.
Financial institutions face $14.8M average compliance breach costs. AI agents are scaling faster than governance — XeroML closes the gap. Plug in, evaluate, prove compliance.
INTEGRATION TIME < 30 min
FRAMEWORKS SUPPORTED 20+
REAL-TIME COMPLIANCE TRACKING
Every agent decision. Audited in real time.
XeroML wraps your AI agents with a compliance observability layer — every decision is logged, mapped to the applicable regulation, and scored before it reaches production. No manual audits. No spreadsheets. No lag.
AI Audit Agent
An autonomous agent reads decision logs, scores against live regulations, and flags violations before regulators do
Regulator-Ready Outputs
Adverse action notices, audit packs, and CCO reports — auto-generated in seconds, not weeks
USER / REQUEST
REQUEST.RECEIVED()
KYC submission, loan approval, or fraud check enters your AI workflow.
AGENT
AGENT.EVALUATE()
Agent analyzes context, reasons over policy, and proposes a decision with evidence.
DECISION.PROPOSE()
CONTEXT.SUMMARY()
COMPLIANCE SDK INTERCEPT
RULE.VERIFY()
SDK intercepts the decision in real time and checks ECOA, SR 11-7, Fair Lending, and BSA/AML rules before execution.
APPROVE / BLOCK
COMPLIANCE.FLAGS
AUDIT.TRAIL
REASONING.LOG
SYSTEM / RECORD
DECISION.EXECUTE()
Approved decisions run, blocked actions halt, and every outcome is sealed in immutable logs.
Agent decision flow
XeroML intercept at step 3
Real-time compliance evaluation
END-TO-END EVAL & TRACING
See every step. Score every output.
Full Workflow Traces
Trace ML pipelines, LLM calls, retrieval steps, and agent decisions in a single view
LLM Judge Evaluation
Calibrated judges score every output for accuracy, grounding, compliance, and coherence
Real-Time Monitoring
Latency, token cost, eval scores, and drift detection across every agent run
Xeroml Trace Explorer
The fastest way to evaluate, debug, and improve your financial AI workflows.
Explore Trace Explorer-
Connect your agent
Drop in our SDK with 3 lines of code. Supports LangChain, LlamaIndex, CrewAI, custom frameworks, and any OpenTelemetry-compatible pipeline.
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Configure LLM judges
Calibrated judges score factual grounding, numerical accuracy, bias/fair lending, and reasoning coherence. Failing scores block deployment.
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Set compliance rules
Map regulatory requirements to automated checks — fair lending, advisory, PII masking, data protection. Flag decisions lacking explainability.
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Deploy to production
One Docker Compose command deploys Xeroml inside your VPC. No external dependencies, no data egress — production-ready in under 30 minutes.
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Monitor & improve
Live dashboards for traces, eval scores, and compliance checks. Low scores surface prompt fixes automatically.
COMPLIANCE INTELLIGENCE
Score every decision. Prove compliance.
Regulatory Scoring
Automated checks mapped to RBI, SEBI, ECOA, and Basel III — every agent output scored before it reaches production
Explainability Reports
Generate ECOA-compliant adverse action notices and audit-ready reasoning trails for every AI decision
Drift Alerts
Statistical drift detection (PSI, KS tests) triggers alerts when agent behavior deviates from approved baselines
Compliance Intelligence
Scores every agent decision against your regulatory frameworks, surfaces explainability gaps, and generates audit-ready reports.
Explore Compliance Engine-
Regulatory scoring
Every agent output is checked against your compliance rules — fair lending, advisory suitability, KYC, PII masking. Failures block production.
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Explainability reports
Auto-generate audit-ready reasoning trails for every flagged decision. One click to export for regulators.
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Drift detection
Continuous monitoring compares agent behavior against approved baselines. Get alerted the moment output distributions shift.
CONTINUOUS IMPROVEMENT
Your agents get better with every run
Regulatory Judges
ECOA, TILA, SR 11-7, and fair lending judges score every agent output before it reaches production
Backtest & Validate
Champion-challenger testing against historical decisions — verify SR 11-7 thresholds before promoting to production
Audit Trail
Every improvement logged with timestamps, score deltas, and approvals — exportable for SR 11-7 model governance audits
The Regulatory Improvement Loop
LLM judges mapped to ECOA, TILA, and SR 11-7 score every output. Violations are diagnosed, fixes backtested against historical decisions, and every improvement is audit-logged.
See How It Works-
Regulatory judge scores
Every agent output scored by judges mapped to ECOA, TILA, SR 11-7, and fair lending frameworks. Failures block deployment.
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Violation diagnosis
When a regulatory judge fails, Xeroml identifies the specific violation, traces the root cause, and generates a regulation-compliant prompt fix.
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Backtest & validate
Apply the fix, run champion-challenger testing against historical decisions, compare before/after across all judges, then promote.
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Improvement audit trail
Every fix logged with timestamps, score deltas, and approvals. Export the full trail for SR 11-7 audits.
REQUEST EARLY ACCESS
Stop wondering if your AI agents will pass the next regulatory exam.
XeroML gives compliance teams real-time proof that every AI decision meets ECOA, TILA, SR 11-7, and Fair Lending requirements. Deployed in your VPC in under 30 minutes. No data leaves your infrastructure.