Built for life sciences companies managing lot traceability, expiration windows and compliance holds without slowing execution.
A lot approaches its expiration window before it's been allocated to an order, so teams need to decide how to move it before it becomes unusable.
A shipment's temperature moves outside its approved range, so teams need to pull it from circulation and route it to quality review for a formal decision on what happens to it next while taking steps to avoid this in the future.
A lot is placed on regulatory or quality hold, so teams need to decide what's blocking release and how to resolve it.
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Compliance failures in life sciences don't show up as a missed SLA. They show up as a hold that doesn't clear, an excursion that isn’t contained or a lot that expires before it moves. Our checklist for evaluating an AI supply chain execution solution outlines the questions that matter when execution and compliance can't be treated separately.
A lot shouldn’t lose its chain of custody as it moves across orders, warehouse operations and transportation. Infios AI works inside those execution systems, helping teams maintain traceability, surface issues as they happen and coordinate the response before they become a compliance or service problem.
Predictive, generative, agentic and conversational AI work together across every lot and every shipment: sensing an expiration or compliance risk early, deciding what needs a hold or an escalation, coordinating the order, warehouse and transportation response and getting more precise about what counts as a risk with every batch that moves through.
Life sciences companies don't need to tackle every compliance workflow at once. A good starting point is Order Error Diagnostic agent: instead of a quality or logistics team manually tracing why a lot is held or an order is blocked, Infios AI investigates the root cause and recommends what needs to happen next. From there, autonomy can expand into expiration management and excursion response.
Not every hold carries the same level of risk, so it shouldn’t get the same level of oversight. Life sciences teams apply their own approval rules by product, hold type or regulatory requirement, keeping a person in the loop for the decisions where a signature means something, while Infios AI acts independently to speed up everything around that decision, not the decision itself.
capacity increase in the automated storage & retrieval area
increase in picking performance
capacity increase in the automated storage & retrieval area
increase in picking performance
