Runtime Enforcement By Design
Define and enforce KYC rules, jurisdictional requirements, and data access boundaries at runtime so identity checks behave consistently as regulations and models change.
Run KYC agents in production with predictable behavior, enforced compliance boundaries, and audit-grade accountability.
Inconsistent confidence thresholds for the same document types from different customers
LLM extraction varies by model version, prompt, and context window
Risk indicators differ across runs, undermining confidence in KYC scoring
Non-deterministic LLM behavior yields different normalized outputs
Same customers are flagged differently on re-review creating regulatory and audit risk
Without runtime enforcement, policy rules are interpreted differently by agents
Decisions cannot be traced back to source evidence during audits
AI outputs lack provenance across document inputs, prompts, and model calls
Agents don’t trigger EDD consistently (over/under reporting) creating compliance issues
Escalation logic lacks visibility into agent reasoning and confidence
Define and enforce KYC rules, jurisdictional requirements, and data access boundaries at runtime so identity checks behave consistently as regulations and models change.
Ensure identity extraction and risk signals are consistent across runs, models, and document variations.
Architect agents to automatically record inputs, decisions, and evidence used in KYC determinations, producing audit-ready records by default.
Define, enforce, and evolve agent performance metrics as models, context, and workflows change.
1.
Define operational boundaries
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Enforce behavior at runtime
4.
Prove readiness continuously
3.
Expand autonomy safely
1.
Approved identity sources, risk signals, escalation thresholds, and jurisdictional rules. Clear limits on what KYC agents may determine autonomously.
LLM and MCP catalog with approved resources and access policies
2.
Validate identity attributes, risk classifications, and decisions before they propagate. Prevent inconsistent policy application and out-of-scope determinations.
Runtime enforcement, prompt blocking, DLP, and consistency checks
3.
Increase automated KYC decisions as confidence and consistency improve. Reduce manual review through controlled, evidence-based delegation.
Readiness standards, automated evaluation pipelines
4.
Maintain evidence that KYC decisions adhere to policy and regulatory requirements over time. Support audits and examinations with records.
Metrics export, traces, audit trails, and compliance reporting
1.
Approved identity sources, risk signals, escalation thresholds, and jurisdictional rules. Clear limits on what KYC agents may determine autonomously.
LLM and MCP catalog with approved resources and access policies
2.
Validate identity attributes, risk classifications, and decisions before they propagate. Prevent inconsistent policy application and out-of-scope determinations.
Runtime enforcement, prompt blocking, DLP, and consistency checks
4.
Maintain evidence that KYC decisions adhere to policy and regulatory requirements over time. Support audits and examinations with records.
Metrics export, traces, audit trails, and compliance reporting
3.
Increase automated KYC decisions as confidence and consistency improve. Reduce manual review through controlled, evidence-based delegation.
Readiness standards, automated evaluation pipelines
Increase customer acquisition without increased risk
Fewer false positives requiring manual review
More consistent KYC decisions across teams
Clear attribution of AI-generated decisions for reviews
Prove how KYC agents behave.
Agent Router Enterprise gives engineering teams the controls, visibility, and accountability required to run credit agents safely in production.