Employee Reimbursement with Compliance Verification

The problem

Reimbursement requests are evaluated before processing. Category-specific rates, documentation requirements, and frequency limits are applied. Compliant requests auto-approve. Over-limit requests escalate to manager with specific violation details. Every decision includes supporting document hash for tax audit traceability.

Without deterministic enforcement, AI agents either block every edge case (adding manual overhead) or silently approve decisions that violate policy — with no audit trail to show auditors or regulators.

How Corules solves it

Corules sits between your AI agent and the action it wants to take. When the agent proposes a decision, Corules evaluates the full context against your compiled policy set in a single deterministic pass — no LLM, no ambiguity.

The result is a structured outcome: ALLOW — Home office equipment $450 within category limit $500. Documentation complete.

Policy example

Corules policies are written in CEL (Common Expression Language). They are compiled once at publish time and evaluated deterministically at request time — no LLM, no variability.

// Reimbursement policy (CEL)
context.amount <= params.reimbursement_rates[context.category]
  && context.documentation_complete == true
  && context.submission_days_after_event <= params.max_submission_delay_days

This expression is evaluated against the structured context your agent sends in the /v1/validate request.

Integration options

Corules integrates with the tools your teams already use. All integrations call the same REST API or MCP server — your policy logic stays in one place.

Frequently Asked Questions