AI Supply Chain Process Automation
Budget / SalaryHourly project
TypeFreelance project
LocationRemote
Posted1 hour ago
I run a mid-sized logistics firm and I’m ready to replace our patchwork of manual workflows with a single, AI-driven automation layer. The goal is to streamline three core areas and have the finished system plug cleanly into our existing WMS and carrier APIs.
What needs to be automated
• Inventory management – predictive reordering to keep stock at optimal levels and an AI-assisted auditing routine that reconciles physical counts with the database in near-real-time.
• Order processing – hands-free order entry from our web store, EDI feed, and email-based purchase orders, plus automatic validation against business rules before anything reaches the warehouse floor.
• Shipment tracking – real-time status updates pulled from multiple carriers, consolidated into a single feed that writes back to customers and our support team.
Tech flexibility
I’m comfortable with Python, Node, or a low-code RPA stack so long as the final solution is well-documented, uses REST/GraphQL where possible, and is future-proof enough to bolt new modules on later.
Deliverables
1. Working automation scripts/services for the three areas above.
2. Clean, version-controlled code (Git) with inline and external documentation.
3. A small dashboard or set of Kibana/Grafana panels that visualise process KPIs.
4. Deployment guide plus a hand-off session to my in-house IT lead.
Acceptance criteria
• Reordering accuracy improves stock-out rate by at least 20 %.
• Order validation flags 95 % of faulty orders before pick-ticket generation.
• Shipment events update our CRM within two minutes of carrier change.
If you’ve built similar AI, ML, or RPA workflows in logistics, let’s talk—I’m ready to start as soon as the scope is locked.
What needs to be automated
• Inventory management – predictive reordering to keep stock at optimal levels and an AI-assisted auditing routine that reconciles physical counts with the database in near-real-time.
• Order processing – hands-free order entry from our web store, EDI feed, and email-based purchase orders, plus automatic validation against business rules before anything reaches the warehouse floor.
• Shipment tracking – real-time status updates pulled from multiple carriers, consolidated into a single feed that writes back to customers and our support team.
Tech flexibility
I’m comfortable with Python, Node, or a low-code RPA stack so long as the final solution is well-documented, uses REST/GraphQL where possible, and is future-proof enough to bolt new modules on later.
Deliverables
1. Working automation scripts/services for the three areas above.
2. Clean, version-controlled code (Git) with inline and external documentation.
3. A small dashboard or set of Kibana/Grafana panels that visualise process KPIs.
4. Deployment guide plus a hand-off session to my in-house IT lead.
Acceptance criteria
• Reordering accuracy improves stock-out rate by at least 20 %.
• Order validation flags 95 % of faulty orders before pick-ticket generation.
• Shipment events update our CRM within two minutes of carrier change.
If you’ve built similar AI, ML, or RPA workflows in logistics, let’s talk—I’m ready to start as soon as the scope is locked.
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