How autonomous is your AI? We created a 5-level framework to find out.

At Fegmo, we needed a better way to talk about how autonomous our AI agents really are.

As we scaled our agentic systems from enrichment through to syndication, we often asked: Is this fully automated? When does it ask for help? Do I need to supervise it?

That’s when we realized we needed a shared vocabulary around autonomy.

So we created the SCALE Framework - a simple, 5-level model to describe how agentic workflows behave and evolve:

Suggest [Level 1] – Agent provides recommendations only
Confirm [Level 2] – Agent acts after approval
Act with Escalation [Level 3] – Agent acts, escalates when unsure
Low-Touch Autonomy [Level 4] – Agent acts independently, escalates only edge cases
End-to-End Autonomy [Level 5] – Agent manages the entire task lifecycle with optional oversight

SCALE is helping teams align, set realistic expectations, and design workflows that evolve responsibly toward greater autonomy. At Fegmo, it’s not just a language, it’s shaping how we build.

This sprint, we’re applying SCALE to advance our bulk enrichment workflows toward Level 4 autonomy, where agents process millions of SKUs with minimal oversight and surface exceptions for our review when needed.

The agentic era is not just coming, it’s being shaped. If you’re building with AI, adopting a shared framework like SCALE can help you scale responsibly, communicate clearly, and unlock real operational trust.