Leobit
Grain Trading and Logistics Operations Platform
Software reengineering and custom web development for a grain trading and logistics company that resulted in replacing a legacy desktop system with a centralized web platform without interrupting daily operations
ABOUT the project
- Client:
- Farm Equipment Supplier
- Location:
-
Ireland
- Company Size:
- 50+ Employees
- Industry:
-
Agriculture
- Solution:
- Custom Software Development
Leobit is helping the customer modernize the software behind its grain trading and logistics operations. Our team is developing a web-based operations platform that will gradually replace a legacy desktop system while improving inventory visibility, automating calculations, and bringing processes currently managed through emails and spreadsheets into a single application.
Because the existing system remains essential to daily operations, Leobit designed a phased modernization strategy in which the old and new platforms operate in parallel. Business processes move to the new platform one by one until the legacy application can be retired. The project has progressed from Discovery and architecture design into active product development, and the team is approaching the first internal release, which will let the client test the initial end-to-end workflow before a broader production rollout.
Based on the business analysis, we redesigned the solution’s core workflows, modernizing the technology while simplifying how customers moved through them. That gave the client new capabilities built on top of their legacy system, all introduced without disrupting daily operations.
Customer
Our customer is a grain trading and logistics company which sources, purchases, sells, imports, and delivers cereals and feed ingredients. Its operations extend well beyond transport. The company purchases and sells grain, trades through brokers, sources products from international suppliers, organizes freight and maritime transportation, manages grain unloading and storage, coordinates deliveries, and monitors supply, demand, inventory, and customer balances. These interconnected activities require the company to manage contracts, shipments, inventory, logistics, financial balances, and market information across multiple stages of the grain supply chain.
Business Challenge
The customer relied on a legacy system from the 1990s and early 2000s: Windows Forms desktop applications, a shared SQL Server database, and an Azure virtual machine. Business logic sat in the desktop clients and the database, so even standard automation and integrations were hard to add. Many workflows ran entirely through emails, spreadsheets, and manually maintained records. With no centralized view of grain inventory across ports, storage locations, and regions, managers could not quickly determine how much stock was available, allocated, or likely to last.
Why Leobit
The customer chose Leobit for its expertise in legacy application modernization and its ability to deliver complex business transformation projects. Beyond replacing outdated technology, the engagement required redesigning critical business processes, introducing a modern cloud-based architecture, and planning a gradual migration strategy that would allow the business to continue operating throughout the transition.
Project
in detail
We started our cooperation with a detailed requirements gathering and the customer’s legacy platform analysis.
Process redesign for greater efficiency. Rather than simply transferring existing workflows to a new technology stack, our team used the modernization as an opportunity to simplify and improve them. We reviewed each process to identify which steps delivered real value, which could be combined, which calculations could be automated, and where AI-assisted functionality could support future improvements. In one representative workflow, this approach reduced a ten-step process to four streamlined steps.
Our team designed a consolidated inventory model that shows stock by port, region, storage location, product, customer, contract, and shipment. Information previously scattered across emails, spreadsheets, database fields, and free-text notes now lives in a structured model that gives managers a clear view of current inventory, available and reserved stock, expected supply, customer demand, planned deliveries, and stock movements.
Many values in the legacy system were stored as unstructured text, notes, or loosely connected records. Leobit experts converted this information into dedicated business entities with defined relationships: grain products, contracts, customers, suppliers, storage locations, ports, shipments, inventory records, planned deliveries, and customer balances. The normalized model makes information easier to validate, search, calculate, report on, and use in future automation.
The platform automates the calculations triggered when a user creates or updates a contract. Instead of manual recalculation, the system propagates changes across related records: contract quantities, allocated inventory, available stock, customer balances, supply commitments, planned deliveries, and shipment data. These cascading calculations maintain consistency across the system and reduce the errors that come from updating several spreadsheets by hand.
The platform adjusts customer balances when transactions, contracts, allocations, or deliveries change, and recalculates stock levels as business events occur. Employees see a current view of each customer’s position and of how much grain is available, reserved, in transit, expected to arrive, or allocated to specific contracts.
The customer sources a substantial share of its grain internationally, with deliveries arriving by sea. Our team introduced a shipment scheduling module that centralizes vessels, planned shipments, expected arrival dates, ports, cargo quantities, shipment statuses, unloading stages, associated contracts, storage destinations, and delivery plans. Status changes can trigger corresponding updates in related parts of the system.
The platform calculates how long current inventory is expected to last, drawing on historical consumption, current stock levels, expected demand, customer commitments, planned shipments, and incoming supply. These run-rate calculations help managers spot potential shortages, excess stock, and purchasing requirements earlier, and they establish the data foundation for more advanced predictive analytics in later phases.
By connecting contracts, inventory, shipments, and customer requirements, the system lets managers compare available stock against current commitments, incoming supply against forecast demand, and expected stock positions for future periods. This replaces fragmented calculations previously performed in spreadsheets and email threads.
The Angular and PrimeNG front end replaces locally installed Windows Forms applications with a centralized browser-based interface: consistent access to the latest version, centralized deployment, a clearer user experience, and a foundation for access from different devices.
Leobit’s design team created UI concepts for the highest-priority modules identified during Discovery and built lightweight prototypes that let the client visualize redesigned workflows, compare the legacy and future systems, and validate requirements before development. The prototypes showed that the opportunity extended beyond a visual refresh, and they helped the customer confirm its decision to comprehensively rebuild the platform.
Discovery in two parallel tracks
Leobit began the engagement with a Discovery Phase that combined business process analysis with technical discovery and architecture planning.
The business analysis team conducted surveys and interviews with users of the existing application to understand how they used it in practice. The team mapped current processes, documented activities handled outside the system, identified pain points, and prioritized the workflows to be implemented first.
In parallel, the technical team reviewed the legacy application, source code, database structure, security limitations, and performance risks. Based on these findings, the team defined the target architecture, technology stack, data models, integration approach, and migration strategy.
The Discovery Phase resulted in current-state and future-state process maps, a prioritized feature catalog, user stories, preliminary estimates, architecture documentation, UI/UX prototypes, and a phased implementation roadmap.
Legacy system integration
A complete immediate migration was not practical because the existing application still supports essential workflows that have not yet been rebuilt. Leobit therefore designed an integration layer that allows the old and new systems to operate in parallel.
Operational data must move between the platforms with a delay of no more than several minutes. The target integration uses Change Data Capture to identify database changes, Debezium to capture and publish change events, and Azure Event Hubs to transmit events between the systems. This approach allows the new platform to detect relevant changes without repeated full-database imports.
The migration is more complex than copying data from the old system into the new one, because some business entities move between platforms during their lifecycle. A record may be created in the legacy application, processed through several stages in the new platform, and then returned to the legacy system for a later stage, after which the updated information must remain consistent in both environments. The integration, therefore, preserves entity states, relationships, and ownership as processes move between the two applications.
During early development, the team used a more manual, on-demand synchronization approach to validate workflows and data mappings. The production-oriented infrastructure detects database changes automatically, transfers updates with minimal delay, keeps corresponding records consistent, and supports the gradual movement of workflows between systems.
Implementation strategy: vertical process migration
Leobit adopted an incremental migration strategy rather than a high-risk, all-at-once replacement. The legacy and new systems coexist while functionality moves in phases: at the beginning, the new platform supports a limited set of processes, and each subsequent phase transfers additional workflows until the legacy system is no longer required.
The first release focuses on a complete vertical workflow rather than small fragments distributed across the application. The objective is to let at least one user complete an end-to-end process in the new platform without returning to the legacy application for that workflow. This delivers usable business value earlier, validates the complete technical architecture and synchronization mechanism, generates feedback before broader rollout, and reduces migration risk.
The current phase establishes the platform foundation: architecture, data model, user interface, core business entities, inventory logic, contract calculations, legacy synchronization, and Azure infrastructure. More advanced automation and AI-supported capabilities will follow once the fundamental workflows and data structures are stable. The customer stays closely involved throughout: the client regularly reviews implemented functionality, validates workflows, reprioritizes features, and tests prototypes and early versions. Instead of designing around the limitations of the legacy system, stakeholders can now consider what the business actually needs from the new platform.
The Journey
Behind Our Success
Technology Solutions
- Adopted PostgreSQL as the database for the new platform and designed a normalized data model around the company’s contracts, inventory, shipments, customers, and operational processes.
- Used Angular and PrimeNG to replace locally installed Windows Forms applications with a modern web-based interface.
- Deployed the front end and back end through Azure Web Apps for centrally managed, scalable application hosting.
- Implemented Change Data Capture to identify updates in the legacy SQL Server database.
- Integrated Debezium to convert database changes into events that the new platform can process.
- Used Azure Event Hubs to support near-real-time data exchange between the old and new systems.
- Adopted a single-tenant monolithic architecture that matches the client’s current operational scale while keeping the codebase straightforward to develop, deploy, and maintain
Value Delivered
- Helped the customer formalize and document business processes that had developed over many years and were not always fully understood across the organization.
- Reduced process complexity by redesigning workflows instead of reproducing legacy ones
- Reduced manual calculation through automated cascading updates to contracts, stock levels, customer balances, and related records.
- Established a reliable modernization path: parallel operation of the legacy and new systems lets the company modernize gradually without interrupting essential operations.
- Created the technical foundation for future predictive analytics and AI-assisted workflows through structured data, normalized entities, event-based synchronization, and a modern back end.
