RedHub AI
How the gate works
How the Agent Use-Case Fit & Proof-of-Value works
This tool grades a proposed AI agent on six use-case-fit dimensions, then runs the money against the controls before you spend the build budget. It scores 6 weighted controls into a 0–100 number — then a gate that can only make the verdict worse.
The 6 weighted controls
Two worsen-only structural gates sit on top of the fit score. If the projected return doesn't survive the mitigation the agent needs — controls, validation, human oversight — net return is zero or negative and the verdict is DON'T BUILD. If there is no genuine autonomy need (automation rebranded as an agent), same result. Either gate forces DON'T BUILD no matter how high the fit score; the score never grants permission to build.
Why: This refund-and-dispute agent marks CLEAR on almost every dimension — the fit score is 94, which alone reads BUILD. But the money doesn't work: $140k of required mitigation outruns its $120k projected return, so net return is -$20k. The mitigation gate forces DON'T BUILD; a high fit score can't rescue money that doesn't clear.
A high score didn’t save it. The score is context; the gate is the answer — and it names the one thing to fix first. A planning decision aid, not advice. It scores the proposal you describe from your own numbers; it never builds or runs an agent and scores no person. Confirm your own cost and return estimates. Not financial, investment, or legal advice.