Core Banking Modernization
Stop worrying about the dangers of replacing your entire banking system at once. We use a step-by-step approach that wraps your old systems in modern, high-speed software. This gives you a massive boost in performance and speed while keeping your bank online and 100% available at all times.
Modernize without the downtime risk
550+ Engagements Since 2006 — Trusted By
Legacy core banking systems often cause high latency, frequently exceeding 500ms. These systems are difficult to scale and act as bottlenecks that block innovation. Traditional modernization approaches are often avoided because they require risky big-bang migrations that can disrupt entire banking operations.
CUSTOMER STORIES
Client Results and Success
RESULTS DELIVERED
Business Impacts We Have Made
56%
Latency Reduction
We dropped API response times from 500ms to 220ms, enabling real-time responsiveness for legacy core systems that previously throttled user experience.
10x
Performance Boost
High-performance Golang wrappers process requests ten times faster than legacy SOAP/XML calls.
100%
System Uptime
We ensure zero-downtime modernization. Legacy operations continue uninterrupted while we shift traffic to new services.
+40%
Developer Velocity
By replacing rigid legacy code with modern microservices, our engineering teams deploy new features faster, reducing time-to-market.
WHAT WE DO
Our Customer Experience and Onboarding Services
Strangler Fig Pattern Implementation
We incrementally replace legacy monolithic functions with modern microservices. This avoids risks by wrapping legacy OBP and FlexCube systems in high-performance Golang layers.
SOAP/XML to gRPC/REST Conversion
We modernize the communication protocol of your core. Our centralized OBP Proxy Service handles complex XML transformations, exposing clean REST APIs for frontends and gRPC for internal services.
Multi-Tier Redis Caching
We implement intelligent caching strategies with optimized TTLs. This reduces the load on the core banking system by serving frequently accessed data directly from high-speed memory.
Traffic Shadowing and Verification
Before going live, we use traffic shadowing to test new services with real-world production data. This validates performance and logic without affecting the live user experience.
Connection Pooling Optimization
We re-engineer how your application interacts with the core database, preventing connection exhaustion and ensuring stable performance during peak transaction periods.
Independent Service Scaling
By containerizing modernized functions with Kubernetes, we allow individual banking modules (like Payments or Ledgers) to scale independently based on demand.
OUR OFFERINGS
Engineering Digital Banking for Global Enterprises and Agile Startups
Customer Experience and Onboarding
We help enterprises acquire customers faster without compromising compliance or security.
Core Banking Modernization
By re-architecting infrastructure and optimizing data pipelines, we enable faster customer interactions and real-time processing.
Retail Banking Services
Our solutions focus on intuitive UX, secure authentication, and high availability to support peak traffic without performance drops.
Loan Services and Credit
We integrate KYC, risk scoring, and audit trails to ensure transparency and regulatory compliance.
TECHNICAL HIGHLIGHTS
Core Banking Modernization Services by Engineers Who Have Delivered 1000+ Projects
Production-proven implementations with enterprise-grade architecture.
Microservices Layer
Internal Communication
Frontend API Surface
Caching Architecture
Infrastructure
Compliance

FEATURED CONTENT
Our Latest Thinking in Core Banking Modernization
Discover the latest blogs on Our Latest Thinking in Core Banking Modernization, covering trends, strategies, and real-world case studies.

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Apr 17, 2026
How to De-Risk AI Product Investments Before Full-Scale Rollout
Most AI pilots never reach production, and the reasons are more preventable than teams realize. This blog walks through the warning signs, the safeguards, and what structured thinking before the build actually saves.

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Credit Card Fraud Detection and Prevention Strategies for Businesses in the USA
Credit card fraud costs U.S. businesses billions. Discover proven prevention & detection strategies using secure architecture, AI, and compliance to stay ahead of evolving threats.

Technology
Sep 24, 2025
The Three Pillars of Digital Trust: Encoding, Hashing, and Encryption
Confused about encoding, hashing, and encryption? This cybersecurity guide explains how to protect data and ensure digital system trust.

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How Workflow Automation Powers Scalable Digital Platforms
Workflow automation is the hidden backbone of scalable digital platforms. See how automation with AI ensures resilience, efficiency, and seamless experiences.

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Sep 22, 2025
Beyond Throttling: Rate Limiting as a Strategic Layer in Modern API Systems
Discover why rate limiting is more than throttling. Learn strategies, algorithms, and architectures that keep APIs resilient, fair, and scalable.

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Nov 8, 2024
AI as a Catalyst for Digital Transformation and Expansion
Explore how AI powers digital transformation, drives business growth, enhances customer personalization and boosts operational efficiency across industries.
Build with us.Accelerate your Growth.
Customized solutions and strategiesFaster-than-market project deliveryEnd-to-end digital transformation services
Trusted By
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Build with us.Accelerate your Growth.
- Customized solutions and strategies
- Faster-than-market project delivery
- End-to-end digital transformation services
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What You Need to Know
FAQs About Our Core Banking Modernization Service
The Strangler Fig Pattern is an incremental migration approach where new services are built alongside the existing system rather than replacing it all at once. Each new microservice takes ownership of one domain, account queries, transaction lookups, and balance checks, while the legacy system continues handling everything else. Over time, the legacy system's responsibilities shrink until it is either fully replaced or isolated to a minimal footprint. In core banking, this approach is used because a big-bang replacement requires a cutover window where the system is unavailable. For a bank processing live transactions, that window is not acceptable.








