Offer Approval with Compensation and Equal Pay Coruless

The problem

Compensation offers are validated before extending to candidates. Corules checks the proposed salary against the role's pay band for the location, flags offers significantly below market median (potential bias signal), and escalates offers exceeding recruiter authority to the compensation committee. Every offer decision logs the band data version used.

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: ESCALATE — Proposed salary $72K below p25 ($78K) for role/location. Flagging for compensation review — potential equity concern.

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.

// Offer approval policy (CEL)
context.proposed_salary >= params.pay_bands[context.role][context.location].min
  && context.proposed_salary <= params.pay_bands[context.role][context.location].max
  && context.proposed_salary >= params.pay_bands[context.role][context.location].p25

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