Overview

GlobalEdge Enterprises, a multinational business services provider, managed multiple legacy systems across departments for HR, finance, and operations. This fragmented infrastructure resulted in data silos, limited collaboration, and manual inefficiencies, ultimately slowing down decision-making.
Operating across multiple regions and business units, GlobalEdge had accumulated more than a decade of departmental software choices that no longer talked to each other. HR ran on one stack, finance on another, and operations on a third, with critical data flowing between teams through spreadsheets, exported CSVs, and email attachments. Month-end reporting routinely took two to three weeks, leadership lacked a single source of truth for KPIs, and the engineering team spent the majority of its sprint capacity maintaining brittle integrations rather than building new features. The fragmentation was no longer just an inconvenience; it was a measurable drag on growth, audit readiness, and customer responsiveness.
The company partnered with Bacancy to design and develop a custom enterprise SaaS platform that unified core business functions, automated workflows, and delivered actionable insights. The mandate was to consolidate HR, finance, and operations onto one multi-tenant SaaS platform with shared identity, shared data, and analytics; replace manual handoffs with event-driven automation; and put real-time dashboards in the hands of department leads so decisions stopped waiting on reports. The goal was to achieve scalability, reduce operational costs, and improve overall business agility while ensuring data security and compliance. Equally important, the new platform had to meet GDPR and ISO 27001 controls from day one, support the company’s planned expansion into new regions without re-architecture, and give the in-house team a foundation they could extend on their own roadmap after Bacancy’s engagement closed.

Technical Stack

  • PostgreSQL
  • Amazon EC2
  • Amazon S3
  • RDS
  • Jenkin
  • Kubernetes
  • React.js
  • Node.js

    • Industry

    Information Technology

  • region

    • Region

    North America

  • project-size

    • Project Size

    Non-Disclosable

Challenges & Solutions

Disconnected Legacy Systems Across Departments

GlobalEdge’s HR, finance, and operations stacks had been built or acquired separately over many years and had never been designed to share data. A new hire onboarding, for example, touched three systems manually, and a single payroll cycle pulled data from four. Every integration was a custom point-to-point script that broke whenever any vendor pushed an update, and the engineering team was spending the majority of its bandwidth firefighting these integrations instead of building new features.

  • Solution: Our software developers engineered the entire architecture into a unified microservices-based SaaS platform, allowing independent module deployment. This ensured seamless data flow across departments, improved interoperability, and reduced integration costs. Each business domain (HR, finance, operations) was modeled as its own bounded context with a dedicated service, a shared event bus handled cross-domain communication asynchronously, and a unified identity layer replaced the three separate auth systems. The tradeoff was a heavier upfront design phase to define service boundaries cleanly, but it eliminated the brittle point-to-point integrations and gave each team independent deployment velocity.

Limited Scalability During High Transaction Loads

The legacy systems were vertically scaled and started degrading whenever monthly reporting, payroll runs, or quarter-end close concentrated traffic. Users would see timeouts on dashboards, batch jobs would silently fail, and operations would lose hours rerunning failed jobs. Horizontal scaling was not possible on the original infrastructure without a full re-platforming.

  • Solution: Using AWS auto-scaling groups and containerized workloads via Kubernetes, Bacancy ensured dynamic scalability. The platform efficiently handled spikes in concurrent user activity without downtime or performance degradation. Stateless services were containerized and deployed on Amazon EKS with horizontal pod autoscalers tied to CPU and request-rate metrics, while RDS read replicas absorbed read-heavy analytics traffic. The tradeoff was investing in observability tooling early (CloudWatch, Prometheus, and Grafana) so the team could trust the autoscaler decisions, but the result was a platform that absorbed month-end load spikes without manual intervention.

Data Security and Compliance Requirements

Operating across multiple regions meant GlobalEdge had to meet GDPR obligations for European users and ISO 27001 controls for enterprise contracts. The legacy systems had inconsistent access controls, no central audit trail, and stored several categories of sensitive data in plaintext, which was a hard blocker for the new platform and a real risk for the existing one.

  • Solution: The platform was developed with role-based access control (RBAC), AES-256 encryption, and compliance with GDPR and ISO 27001 standards. Secure APIs and encryption ensured all sensitive business data remained protected in transit and at rest. A centralized RBAC service powered every authorization decision, AWS KMS managed encryption keys with automated rotation, and all administrative actions were emitted to an immutable audit log. The tradeoff was strict additional latency on a small number of administrative endpoints, but in exchange, GlobalEdge cleared its compliance audits on first review and significantly reduced its exposure to data-incident risk.

Manual Workflow Bottlenecks and Reporting Delays

Approvals for expenses, leave, vendor onboarding, and procurement all moved through email and spreadsheets, and month-end reporting required analysts to manually reconcile data pulled from each legacy system. Department heads were routinely making decisions on numbers that were a week or more stale, which was the single biggest complaint surfaced in the discovery interviews.

  • Solution: By integrating AWS Lambda for serverless automation and building custom workflow orchestration modules, the team eliminated manual dependencies. Real-time analytics via AWS QuickSight enabled department heads to make faster, data-driven decisions. A custom workflow engine modeled approvals as configurable state machines, AWS Lambda handled the long tail of integrations and notifications without dedicated infrastructure, and our data warehouse services supported a near-real-time reporting setup fed by CDC streams from the operational services. QuickSight dashboards refreshed against this setup, giving department heads access to live data instead of weekly stale reports. The tradeoff was Lambda cold-start latency on rare paths, mitigated with provisioned concurrency on the highest-traffic functions.

Core Features

  • Multi-Tenant SaaS Architecture for scalable enterprise operations
  • Workflow Automation Engine for cross-department coordination
  • Real-Time Analytics Dashboard for deeper actionable business insights
  • End-to-End Security & Compliance with AWS IAM and encryption
  • CI/CD Deployment Pipeline with advanced Docker & Jenkins integration
  • Seamless Cloud Integration using AWS Lambda and API Gateway

Results & Impact

Within seven months of the engagement, the new platform delivered measurable improvements across efficiency, reliability, security posture, and team velocity.

  • 99.99% platform uptime achieved through multi-AZ AWS deployment, Kubernetes self-healing, and automated failover for the data tier.
  • Month-end reporting cycle reduced from 2–3 weeks to under 48 hours through real-time analytics dashboards and automated data pipelines.
  • Zero data security incidents since launch, with full GDPR and ISO 27001 compliance cleared on first audit.
  • Deployment frequency increased from monthly to multiple times per week after standardizing on Jenkins, Docker, and Kubernetes blue-green deployments.
  • Single source of truth established across HR, finance, and operations, eliminating the manual CSV reconciliation work that had previously consumed dozens of analyst hours every month.
  • no.-of-resources

    • No. of Developers

    07

  • time-frame

    • Time Frame

    Feb 2025 - Sep 2025

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