What

Handled is an AI operations automation product for commerce brands and 3PLs. It is positioned as an “AI teammate” that learns existing operating workflows and executes recurring operations work across order processing, shipment tracking, returns, and invoice reconciliation.

The product is designed for teams managing growing transaction volume without adding proportional headcount. Its core workflow is: connect current systems, train on team-specific processes and exception patterns, then automate execution with human escalation for edge cases.

Features

End-to-end returns processing: Automates return initiation, inspection, disposition, restock actions, WMS updates, and customer notifications to reduce manual handling.
Shipment tracking and exception resolution: Monitors carrier activity in real time and handles delays, delivery failures, and related actions such as reroutes, reships, and carrier claims.
Forecasting and inventory intelligence: Tracks inventory health across warehouses and channels, flags stockout risk in advance, and supports reorder point calculations.
Invoice reconciliation and AR automation: Performs three-way matching (PO, receipt, invoice), flags discrepancies, schedules payment reminders, and helps maintain AR aging.
Wholesale order lifecycle automation: Processes POs from EDI, email, and portals, then manages allocation, fulfillment routing, shipment tracking, and invoicing.
3PL and carrier performance management: Tracks SLA/OTIF and quality metrics with automated scorecards, trend alerts, and support for credit claims.

Helpful Tips

Prioritize one high-friction workflow first (for example returns or shipment exceptions) to validate process fit before expanding to broader automation.
Confirm data quality and ownership across ERP, WMS, EDI, and carrier inputs early; automation quality is directly tied to source-system reliability.
Define clear escalation rules and approval thresholds so teams know when the system acts autonomously versus when humans intervene.
Treat published outcomes as directional benchmarks; expected gains should be modeled by your own order volume, exception rates, and channel mix.
Plan change management for operations staff, since value depends on teams trusting exception handling and using standardized SOPs consistently.