WRM organises AI model access through a three-tier stack: providers, models, and availabilities. This page explains how the tiers relate, how credentials are managed, and how worker definitions select which models to use.
Role memories are persistent knowledge entries attached to a role. They allow AI workers to accumulate learning, preferences, and context over time — so that a worker picking up a role does not start from scratch every time.
WRM separates the template for a worker from the running instance. A worker definition is the template; a worker is the instance. This page explains how the two relate, what each contains, and how to create custom worker definitions.
The WRM module provides a unified way to define, configure, and manage workers across your organisation. A "worker" in Raytio is any entity that performs work — a human team member, an AI agent, or an automated service. WRM gives each worker a structured identity and tracks the resources it needs to operate.
Raytio's Worker Relationship Management (WRM) module describes every worker — human or AI — and everything required to spin one up: role, template, system prompt, model stack, and toolset. WRM brings structured worker identity and resource management into the platform with the same encryption, access control, and multi-tenancy guarantees as the rest of Raytio.