Optimization of distributed data management platforms for an international logistics company.
The company had recurring failures in mobile communication for its field teams, with an average latency of 450 ms in critical data transmission. The distributed server infrastructure operated with 35% idle capacity, generating unnecessary corporate connectivity costs.
We implemented an IT flow analysis using custom automation scripts, evaluating 12 distributed data nodes. A machine learning-based cost control model was applied to identify usage peaks and optimize mobile bandwidth allocation.
Eight Python automation scripts were deployed for real-time monitoring, integrated with the data management API. Six distributed servers were reconfigured, reducing unnecessary redundancy and improving information security in corporate networks through TLS 1.3 encryption.
Technical Report
Latency and performance analysis of corporate mobile network — 45 pages
Dashboard
Real-time monitoring panel with IT flow automation metrics
Source Code
Automation and connectivity cost control scripts — internal repository
Measurable results in security, automation, and connectivity costs.
"Shifumobile audited our corporate mobile communication infrastructure. They detected critical vulnerabilities that no other provider had identified. They implemented solutions that reduced risks by 40%."
"They optimized our distributed data management platform. They automated manual processes that used to take us hours, achieving a 35% operational savings in the first quarter."
"Thanks to shifumobile's courses, our team implemented corporate connectivity policies that reduced mobile communication costs by 28% annually. Tangible results from the first month."