SituationA Fortune 100 investment bank managed a global estate of 60,000+ hosts. Traditional deployment and migration efforts were risky and slow; hidden dependencies caused cascading failures. The institution needed a safe way to modernize without jeopardizing trading operations.
TaskDesign and implement a platform to map, analyze, and manage complex dependencies at scale, reducing operational risk while enabling large migration and consolidation projects.
Action
  • Conceived and architected the ARK platform using population‑based incremental learning for continuous dependency analysis.
  • Built automated impact calculators to simulate migration and upgrade scenarios before deployment.
  • Integrated ARK into global change workflows to provide real‑time risk assessment and decision support.
  • Drove adoption across programs for planned upgrades and emergency remediation.
Result
  • 97% reduction in deployment/migration risk.
  • Safely orchestrated migrations of up to 4,000 hosts at a time across a 60,000+ system estate.
  • 17× operational efficiency improvement versus prior methods.
ReturnEstimated project value: $9M. Realized ROI: $17M via avoided failures, reduced downtime, and accelerated migrations.
YieldARK enabled safe, large‑scale modernization without exposing trading systems to catastrophic risk. It became a cornerstone capability demonstrating how AI/ML‑inspired dependency modeling can deliver safety, speed, and scale simultaneously—reinforcing leadership in adaptive orchestration.
Overview