AI scaling fast with no visibility into model costs or performance. Teams now catch runaway spend and failing models before deliveries slip.
A European parcel logistics company that has doubled its automated locker network to 61,000 in two years, processing 1.4 billion parcels annually and targeting 98% next-day delivery across Europe.
To hit its delivery targets, the company is accelerating AI across logistics forecasting, shopping agents, and software development, but teams lacked...
“Dynatrace gives us real-time visibility across more than 61,000 lockers, helping us maintain consistent service quality as we expand across Europe.”
Automated parcel locker network and out-of-home delivery service for e-commerce.
AI-powered software intelligence platform for observability and application security.
InPost's Operations monitoring is part of this use case:
Related implementations across industries and use cases
Debugging 100-step AI workflows meant manually sifting logs. Now, engineers trace inferences to isolate errors and rapidly deploy models.
Refactoring hundreds of decentralized codebases took days. Now, an AI agent writes and submits code in minutes for human review.
Manually tuning prompts in secure environments was slow and inaccurate. Now, automated feedback loops let engineers refine AI instantly.
Debugging 100-step AI workflows meant manually sifting logs. Now, engineers trace inferences to isolate errors and rapidly deploy models.
Manually tuning prompts in secure environments was slow and inaccurate. Now, automated feedback loops let engineers refine AI instantly.
Complex logistics terms bottlenecked output. AI trained on definitions now drafts posts, helping new hires ramp in three weeks.
Tracking freight required manual portal searches. Now, an AI assistant instantly retrieves real-time shipment data across backend systems.
AI costs scattered across teams with no owner, no baseline. A single view surfaced the true scale—two-thirds was labor, not compute.
Answers scattered across hundreds of SharePoint docs drove repetitive support tickets. An air-gapped AI now surfaces them in seconds.
AI scaling fast with no visibility into model costs or performance. Teams now catch runaway spend and failing models before deliveries slip.
A European parcel logistics company that has doubled its automated locker network to 61,000 in two years, processing 1.4 billion parcels annually and targeting 98% next-day delivery across Europe.
To hit its delivery targets, the company is accelerating AI across logistics forecasting, shopping agents, and software development, but teams lacked...
“Dynatrace gives us real-time visibility across more than 61,000 lockers, helping us maintain consistent service quality as we expand across Europe.”
Automated parcel locker network and out-of-home delivery service for e-commerce.
AI-powered software intelligence platform for observability and application security.
InPost's Operations monitoring is part of this use case:
Related implementations across industries and use cases
Debugging 100-step AI workflows meant manually sifting logs. Now, engineers trace inferences to isolate errors and rapidly deploy models.
Refactoring hundreds of decentralized codebases took days. Now, an AI agent writes and submits code in minutes for human review.
Manually tuning prompts in secure environments was slow and inaccurate. Now, automated feedback loops let engineers refine AI instantly.
Debugging 100-step AI workflows meant manually sifting logs. Now, engineers trace inferences to isolate errors and rapidly deploy models.
Manually tuning prompts in secure environments was slow and inaccurate. Now, automated feedback loops let engineers refine AI instantly.
Complex logistics terms bottlenecked output. AI trained on definitions now drafts posts, helping new hires ramp in three weeks.
Tracking freight required manual portal searches. Now, an AI assistant instantly retrieves real-time shipment data across backend systems.
AI costs scattered across teams with no owner, no baseline. A single view surfaced the true scale—two-thirds was labor, not compute.
Answers scattered across hundreds of SharePoint docs drove repetitive support tickets. An air-gapped AI now surfaces them in seconds.