Solon · AI decision governance
Run a 30-day pilot
Thirty days, one workflow, real decisions. We deploy it, you review it weekly, and either side can walk away.
What we provide
- A deployed stack at your domain, with TLS and your policy repo.
- Policy co-authoring from your current exceptions runbook.
- Reviewer training and a calibration session.
- Weekly metric reviews. The five pilot metrics, no vanity numbers.
What you bring
- A Git repo for your policies. Private is fine.
- Two to four reviewers, typically support managers.
- One integration point for your decision function.
- About 30 minutes a week of feedback.
What we measure
Escalation volume at constant traffic. Rule acceptance rate. Override clustering quality. Evidence completeness. Time from the first override to a merged policy. These are the numbers that tell you whether the loop is working.
How it ends
At day 30 you keep the merged policy, the review history, and the numbers. If the loop worked, we talk about what comes next. If it did not, you have lost nothing but the review meetings.
Run a 30-day pilot
We deploy Solon against your refund or exception workflow. You bring reviewers; we bring the loop and the metrics.
Start a 30-day pilotFree during the pilot · exit anytime · merging stays a human action
Keep reading
- AI decision governance: AI decision governance governs whether a decision was right, not just what an agent can do. Solon learns from human overrides and turns them into versioned policy.
- How Solon turns overrides into policy: Capture every decision, cluster repeated overrides, draft a policy pull request, and keep the merge a human decision. The loop, step by step.
- Refund and exception decisions, made consistent: Goodwill refunds and exceptions vary by manager and shift. Solon makes the precedent explicit, versioned, and consistent across every reviewer.
- Frequently asked questions: What AI decision governance is, how Solon learns from human overrides, what the pilot includes, and what stays a human decision.