Case Study Rework - LatAm Bank
LatAm Bank Saves $24M Annually by Eliminating Legacy Risk
A top-tier Latin American bank came to Devsu looking to eliminate systemic technical debt, reduce operational risk, and regain control over a highly fragmented legacy ecosystem. By deploying an AI-native modernization engine, the bank achieved governed acceleration across its complex digital landscape.
Proven across complex software ecosystems
Fragmented Architecture Limiting
Operational Control
A century of organic growth and acquisitions resulted in a severely fragmented IT architecture comprising over 300 internal applications, many of which were built in COBOL, undocumented, or performing duplicate functions.
The Engineering Situation:
System maintenance consumed a massive portion of the IT budget and engineering bandwidth, forcing teams into reactive firefighting rather than innovation.
35% of applications were redundant or outdated, but a lack of centralized visibility prevented confident decommissioning.
Modernization initiatives routinely stalled due to unclear dependencies and fear of unintended production impact
The Executive Impact:
This structural complexity dragged system uptime down to 98.9%, well below the 99.9% benchmark, leading to recurring disruptions and customer dissatisfaction.
Regulatory audits became slow and resource-intensive due to missing documentation and traceability.
As a result, internal estimates pointed to $80M in annual operational losses driven by inefficiencies, downtime, and unmanaged technical debt.
System Intelligence Driving
Structured Transformation
To eliminate systemic risk without disrupting critical operations, Devsu deployed VelX, an AI-native modernization engine purpose-built for complex, compliance-driven environments.
Rather than approaching modernization as isolated upgrades, the strategy focused on creating a governed, end-to-end transformation layer where every decision was informed by real system intelligence and executed within strict architectural guardrails.
Velx Explorer
Devsu initiated the transformation by establishing full system visibility across the bank’s fragmented ecosystem.
VelX automatically scanned and interpreted over 300 applications, generating a real-time, living inventory of services, dependencies, and data flows.
This intelligence layer replaced months of manual discovery with a continuously updated architectural map, allowing engineering and leadership teams to clearly identify redundancies, isolate high-risk components, and prioritize modernization efforts based on actual system impact rather than assumptions.
By converting opaque legacy environments into structured, queryable intelligence, the bank gained, for the first time, a reliable foundation for confident decision-making.
Velx Architect
With full visibility established, Devsu transitioned into architecture design using AI-generated blueprints aligned with the bank’s regulatory, security, and operational constraints.
VelX Architect translated system intelligence into actionable modernization paths, defining which components should be replatformed, refactored, replaced, or decommissioned.
Each recommendation was validated against compliance requirements and designed to minimize disruption to production environments.
This structured approach eliminated ambiguity in planning cycles, enabling leadership to move from high-level intent to executable roadmaps with precision.
What previously took months of cross-team alignment was reduced to clearly defined architectural decisions backed by data.
AI-Native Delivery
Execution was carried out through a tightly governed delivery model that combined AI acceleration with senior engineering oversight.
Devsu embedded a multidisciplinary team of cloud architects, platform engineers, and modernization specialists to ensure every transformation aligned with the defined architecture.
AI-assisted code transformation and automation pipelines accelerated development, while built-in governance mechanisms ensured that speed never compromised security, compliance, or system integrity.
Key systems, including multi-channel notification platforms and digital card processing engines, were re-architected into scalable microservices, deployed on secure cloud infrastructure, and integrated through distributed messaging frameworks.
Throughout execution, continuous validation loops ensured that every change was traceable, reversible, and aligned with enterprise standards, eliminating the risk of unintended downstream impact.
From Legacy Risk to Measurable
Performance Gains
By converting hidden legacy complexity into structured engineering clarity, the bank eliminated systemic risk and accelerated its modernization roadmap.
Discovery Time
90%
faster system analysis
reducing 3–6 month cycles to under 3 weeks.
Architecture Acceleration
60%
faster solution design
through AI-driven blueprints.
Delivery Velocity
40%
reduction in implementation timelines
cutting 8-month cycles to 12–14 weeks.
Financial Impact
$30M
in annual savings
through reduced waste, fewer outages, and targeted system decommissioning.
*KPIs are benchmarked against traditional software delivery methodologes.
See how Devsu helps engineering leaders eliminate structural uncertainty before scaling their systems.
We saw Devsu not as a vendor, but as an extension of our strategy team. VelX delivered results, but the people behind it helped us reshape how we think about legacy systems.
With a governed engineering foundation in place, the bank has shifted from reactive modernization to continuous, structured evolution. Its digital ecosystem is no longer constrained by legacy risk, but positioned to scale with clarity, speed, and control.
Devsu remains embedded as a strategic partner, working alongside the bank through ongoing advisory and architecture co-design. Together, they prioritize initiatives based on business impact and system dependencies, ensuring every investment strengthens, rather than fragments, the overall architecture.
Through participation in the A(i)dvantage Council, the bank continuously integrates emerging AI-native capabilities and governance frameworks, staying ahead of technological change while maintaining compliance and stability.
Looking forward, the focus is on expanding AI-assisted capabilities across the software lifecycle, enhancing system intelligence, automating validation, and enabling more adaptive, resilient operations.
By sustaining a model of governed acceleration, the bank ensures that growth remains controlled, intentional, and aligned with a long-term architectural vision.
Measurable outcomes in the
systems enterprises depend on
Production launch in 6 weeks
A scalable, cloud-native platform built under extreme time pressure. Speed without sacrificing production-grade quality.
60% faster data processing
A market research platform that needed to re-architect for scale while shipping new AI-powered features. The product squad handled both tracks in parallel.