Inventory planning is a decision-making job disguised as a spreadsheet job: what to reorder, when, from whom, at what quantity, repeated across hundreds of SKUs, every week, forever. Atheera's founders wanted a product where AI didn't just flag the decision but made it, visibly and accountably.
We took Atheera from concept to production: product architecture, the agentic decision engine, and the deployment infrastructure behind it.
The agents monitor stock in real time, forecast demand, and execute reorder decisions autonomously, with the reasoning behind every action logged and inspectable, so a human can audit any decision the system has ever made.
Agentic decision engine
Autonomous agents that monitor, forecast, and act on inventory, bounded by rules the operator sets.
Reasoning & audit layer
Every autonomous action carries its own explanation. Nothing happens that can't be inspected.
Production infrastructure
The full product: model orchestration, integrations, and deployment, built to run unattended.
Atheera went from kickoff to a live product in eight weeks and now executes 200+ inventory decisions a week autonomously, with the reasoning for every action logged and inspectable.
Against the manual planning it replaced, stockouts are down roughly 30% and operators get their planning day back, a result that holds its own against inventory tools that only flag problems instead of acting on them.
“Every tool we looked at would flag a problem and leave the decision to us. Atheera makes the call, shows its reasoning, and it's been right more often than we were. TAP OS took it from an idea to a live product in eight weeks.”