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integrated Supply Chain

  • May 10, 2026
  • 2 replies
  • 32 views

what are the typical use cases that Cognite AI can solve Integrated Supply Chain challenges?

2 replies

Mithila Jayalath
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  • May 12, 2026

@Amman Siddiqi, ​@Richard Resseguie will you be able to help out here?


skdatafusion
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  • May 15, 2026

Hi ​@Prasant Panda,
Thanks for this question.


At Cognite, we are currently working on a supply chain initiative to build a more connected knowledge graph over the top of core cdm offering that can solve complex supply chain use cases. I can talk about one of that here.
 

Integrated Supply Chain Command Centre — De-risking Manufacturing Operations

Supply chain failures rarely come from one event. They happen when maintenance, procurement, and production each hold a piece of the issue — but no one sees the full picture. A machine starts failing. The spare part is backordered. And production needs that machine running at full capacity next week. Three teams. Three systems. Zero visibility into the collision. Our Command Centre connects these dots. It uses a supply chain knowledge graph on Cognite Data Fusion with AI agents that detect these compound risks early, trace the impact across maintenance work orders,  procurement, deliveries, and customer commitments, and recommend trade-offs before the crisis hits.

The AI agents can also find idle spare parts at a sister site before anyone raises a rush order. They prioritise late deliveries by what actually stops production  and not just by invoice value of the spare part. They check if a maintenance job can realistically move forward based on real material availability. Every decision gets full enterprise context instead of guesswork.

We can do this as with an connected supply chain enterprise knowledge graph built directly on the customer's own industrial data.

Hope, I was able to give a context into what we are planning to solve with more connected and complex supply chain use case.

Please feel free to reach out if you need more information on this.