SC-1 — DC Agent Workload Balancing.
Nestlé Vietnam · Posted 2 days ago
Consumer goodsGenerative AI
- Budget
- To be determined
- Timeline
- Based on solution provider proposal
- Apply by
- 22 Nov 2026, 23:59 ICT
Problem statement
A multi-agent AI that balances daily loading volume across CS, Transport and DC: reads notes and cut rules, re-plans at every cut-off and blocks plans over the capacity cap – removing many hours a year of manual balancing. Pilot at one distribution centre.
Expected outcomes and success metrics
- Less manual balancing – measured by hours of manual balancing a year.
- Plans kept within the daily loading capacity.
Target users and impacted teams
- CS (Customer Service)
- Transport
- DC (distribution centre) teams
Data availability and readiness
- Order notes and cut rules
- Daily loading volumes and capacity (named in the summary)
Note: Synthetic data could be potentially provided during the process, upon approval of the Nestlé team and in compliance with data law.
Integration, deployment and infrastructure
To be determined
Note: Nestlé's current environment includes Microsoft Azure and Microsoft Copilot. Solutions that can work with this environment are welcome, and final integration and deployment requirements will be confirmed with the Nestlé team.
Relevant AI technologies
Generative AI
Also: AI agents, Optimisation. Based on Nestlé's description of a multi-agent AI that reads notes and rules and re-plans loading.
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