Skody AI provides AI‑driven production scheduling software tailored for discrete manufacturers, helping them generate optimal, real‑time shop‑floor schedules that adapt to changing demand and resource constraints. The platform integrates with existing ERP and MES systems to automatically prioritize orders, balance workloads, and reduce lead times, enabling factories to increase throughput and on‑time delivery.
Funding
Funding not disclosed
Founders
Product
Problem
Manufacturers of discrete goods often rely on manual or legacy scheduling tools that cannot fully account for machine capacity, labor shifts, and material availability, leading to infeasible plans, missed delivery dates, and excess inventory.
Solution
Skody AI offers an AI‑driven production scheduling platform that creates realistic, conflict‑free schedules for discrete manufacturing lines. The system ingests real‑time data on equipment capacity, workforce shifts, and material inventories, then runs constraint‑based optimization to generate feasible production sequences. Users can view end‑to‑end workflow visibility, adjust priorities, and instantly re‑optimize in response to disruptions such as machine downtime or urgent orders. By aligning schedules with actual shop‑floor constraints, manufacturers can shorten lead times, increase on‑time delivery rates, and maintain tighter inventory control.
Target Audience
Primary customers are discrete manufacturers and factory planners who need to generate feasible production schedules across multiple work centers and shifts.
Features
- Constraint‑aware AI optimizer that balances machine capacity, labor availability, and material flow
- Real‑time data integration from ERP/MES systems for up‑to‑date resource status
- Automatic conflict detection and resolution to prevent infeasible schedules
- Interactive Gantt and board views for easy schedule inspection and manual adjustments
- Rapid re‑optimization engine that updates plans instantly when disruptions occur
- Exportable schedules compatible with common shop‑floor execution systems