PolicyPilot

PolicyPilot is a web app that helps ops and product teams use reinforcement learning to optimize repeatable business workflows (support triage, dispatching, inventory reorder, ad budget pacing) without risking production chaos. You connect historical event logs (CSV, warehouse, or API), define actions and constraints, and the app builds a simulator (“digital twin”) from your data. Then it trains and evaluates RL policies offline, showing expected lift, risk bounds, and where the policy fails. When you’re confident, you can deploy in “shadow mode” to compare recommendations against current decisions before turning on controlled automation. This is an AI app (RL + simulation) with a traditional SaaS shell: data ingestion, governance, and deployment controls. It’s brutally pragmatic: it won’t magically fix bad data or non-stationary processes, but it can produce measurable gains where decisions are frequent, logged, and have clear reward signals.