by Nu10Book a PIE Demo by Nu10The GREAT standard
GREAT is PIE’s operating standard for making intelligent action governed, inspectable, and evidenced against enterprise operating requirements.
A product operating standard
GREAT answers the practical questions around intelligent action: what constrains it, when approval is required, how reasoning is surfaced, what evidence remains, and whether the path can be followed.
Five governance principles
Illustrative enterprise operating scenarios — not customer case studies or performance claims.
Every agent, process, capability, and action operates within defined controls.
A procurement agent prepares a supplier recommendation only within approved policy and spend boundaries.
Policy context and authorised operating scope.
Which policy applied and what the agent was permitted to do.
Risk determines the level of controls, validation, and approval required.
Routine invoice exceptions stay within defined thresholds; unfamiliar or high-value exceptions route to an authorised reviewer.
Risk-based control and escalation.
The risk tier, required validation, and any approval decision.
Context is preserved around what happened, which rules applied, and how an outcome was reached.
A lending analyst reviews the source inputs, relevant rules, and action context behind a flagged decision.
Preserved context and decision rationale.
The inputs, rules, and reasoning context available for review.
The architecture retains evidence for execution, decisions, capabilities, approvals, and policy.
A controller reviews the action, approval, policy, capability, and release context for a consequential run.
Durable run and governance evidence.
The connected record of execution and the controls surrounding it.
Lineage maps business intent through process and capabilities to action and outcome.
A team traces a credit adjustment from request through process, capability, approval, action, and outcome.
Intent-to-outcome lineage.
A connected path across the business and technical operating record.
One provable operating model
Provability becomes durable when it connects how work is authorised, performed, understood, reviewed, and improved—not when oversight is separated from the systems doing the work.
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