For Organizations
Editorial Standards for Teams
Your people are already drafting emails, proposals, reports, and customer messages with AI. We help you train the judgment to evaluate it, write the policy that sets the rules, and define the workflows that decide where AI fits and where a person checks.
Three Pillars of Quality Control
We replace generic prompt engineering with rigorous editorial frameworks. Our engagements build lasting organizational capability through three distinct interventions.
Calibrate Editorial Judgment
Develop Your AI Policy
Define Your AI Workflows
The framework is quick to grasp and takes practice to apply well, so the sessions are built around working real drafts, not reciting steps. We use your genres — client emails, executive summaries, support replies — and the difficult cases: the draft that reads beautifully and says nothing, the statistic that sounds authoritative and is invented, the message that needed a person's voice and got a template instead.
Most companies are using AI every day with nothing written down about how. That blank space is where the real exposure sits — client data pasted into public tools, unverified claims sent under your name, no one sure who's responsible when something goes wrong. An AI policy is the set of standing rules you decide once and apply every time, so your team isn't improvising under deadline.
AI fails quietly when it's dropped into a process with no checkpoints. Defining the workflow puts the judgment in the right place instead of hoping someone catches the problem downstream. This is where AI judgment scales past one person: a good workflow builds the ARED checks into the process, so the standard holds even when the careful reviewer is out that day.
How Engagements Work
Every engagement is scoped to your team, sector, and risk profile. Programs range from a single half-day workshop to a full governance package that combines training, a written AI policy, and defined workflows. Book a free discovery call and we'll figure out what fits.