HybridFull-time· Internship· Internship2026-06-01
The Dataleo angle
The role is relevant because logistics transformation depends on how data, automation and operating-model choices are integrated into governed execution workflows.
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TMS
All Dataleo news, jobs, analyses and tutorials around TMS in Supply Chain and Operations.
3 items · 2 news · 1 jobs · 0 insights · 0 tutorials
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HighIndustrial AI, integrated planning and supply chain execution·2026-06-17
Cognite launches an AI-powered Integrated Supply Chain offering for industrial operations
Cognite has launched an AI-powered Integrated Supply Chain offering designed to connect production, procurement, distribution, logistics and execution. The offer combines industrial data contextualization, connectors to ERP, WMS, TMS and planning systems, semantic models and AI agents that can assess operational constraints in real time.
The announcement extends Cognite’s industrial AI positioning beyond plant operations into end-to-end supply chain decision support. Deloitte and FourKites are involved in the broader ecosystem, reinforcing the link between industrial data, logistics visibility and operational execution.
The value proposition is a more connected view of trade-offs across production performance, supplier commitments, inventory, logistics and customer service, rather than isolated optimization within each function.
The Dataleo angle
This is relevant for Supply Chain AI because it points to a governed decision layer between operational data, planning platforms and execution systems. The critical issue will be ownership of semantic models, shared definitions and trade-off logic across OEE, OTIF, inventory and service.
Before scaling, companies should define which decisions agents may influence, how recommendations are validated and how data lineage is preserved across ERP, WMS, TMS and industrial systems.
Cognite
Medium·2025-07-15
Transportation leaders expect autonomous agents to reshape TMS operations
A Manhattan Associates study found that 61% of organizations expected fully autonomous agentic AI in transportation management within five years, while only 37% had deeply integrated AI and machine learning into their TMS.
The Dataleo angle
The readiness gap highlights the need for data quality, process ownership and controlled automation before autonomous transportation decisions scale.
Manhattan Associates
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