Improved Functionality
The platform’s improved functionality and successful third-party service integrations resulted in faster and more reliable shipping.
Technologies used
Amazon RDS
AWS Codebuilt
Sinatra
React
Circle CI
Vue.js
Motivation
The customer had built a partially working prototype of a logistics platform but needed to enhance functionality, integrate third-party services, fix blockers, and finalize the MVP. The goal was to extend capabilities, optimize performance, stabilize integrations, and ensure the platform could scale across multiple regions.
Main challenges
Challenge 01
Incomplete Third-Party Documentation
The external services the customer selected used different technologies and provided limited documentation. This significantly complicated integration and required reverse-engineering to understand request/response structures.
#1
Challenge 02
Limited Domain Knowledge
The team initially lacked logistics industry experience. They needed time to understand logistics workflows, terminology, delivery pipelines, and domain-specific business rules before contributing effectively.
#2
Challenge 03
Complex Performance & Module Testing
Third-party modules frequently changed input/output structures, and their internal logic was not documented. Testing was challenging due to a distributed microservices & serverless architecture, where one module’s update often broke others.
#3
Our approach
Rapid Familiarization and Team Integration
Our team quickly adapted to the customer’s workflow and processes by participating in all internal meetings. Initial research helped us understand how the third-party modules functioned, and we then joined the project as full members, working remotely.
Feature Enrichment and Bug Fixing
We focused on improving the platform’s existing functionality, including bug fixing, performance optimization, and integrating third-party services. The development process followed modern project management methodologies and included extensive testing to ensure stability.
Microservices and Serverless Architecture
The platform was designed using a mix of microservices and serverless functions, hosted in the cloud to ensure scalability and cost-efficiency. Our engineers integrated multiple services, including data processing and visualization tools, to enhance the platform's overall functionality.
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01
Core API
The Core API serves as the backbone of the platform, managing all incoming and outgoing data from external services, third-party modules, and internal microservices. It ensures that every request, response, and data transformation occurs reliably, providing a unified interface for developers and facilitating seamless communication across the system. The API also handles error reporting, data validation, and integration logic for diverse technologies used by third-party providers.
Key capabilities:
- Integration of multiple third-party services
- Consistent data exchange between microservices
- Centralized communication hub for all platform modules
02
ETL Service
The ETL (Extract, Transform, Load) Service automates the processing of large amounts of incoming logistics data, including CSV uploads, JSON payloads, and API responses from carriers. It extracts relevant information, transforms it into standardized formats, and loads it into cloud-based storage and processing pipelines. By offloading complex data manipulations to cloud functions, this module reduces server load and ensures consistent data availability for analytics and operational services.
Key capabilities:
- Automated data extraction and transformation
- Cloud-based processing for scalability
- Efficient handling of CSV and JSON inputs
03
Front-End Services
The Front-End Services are responsible for creating user-facing interfaces for multiple roles, including brokers, carriers, operators, and administrators. Built with React and Vue.js, these services manage user input, authentication, access control, and real-time updates from the backend. They provide intuitive dashboards, interactive forms, and responsive visualizations that allow users to monitor shipments, update statuses, and generate reports, ensuring a seamless and efficient user experience.
Key capabilities:
- User-specific interface management
- Responsive and interactive dashboards
- Seamless integration with backend APIs
04
Metabase & Analytics Service
This service acts as a central hub for storing and processing metadata and operational data. It enables advanced analytics, custom reporting, and visualization for business users and product teams. By leveraging machine learning features, the service can provide predictive insights, detect anomalies in shipping processes, and generate actionable reports that improve decision-making and operational efficiency across logistics workflows.
Key capabilities:
- Storage of structured and unstructured metadata
- Custom visualizations and report generation
- ML-assisted analytics for predictive insights
05
Machine Learning Features
Machine Learning modules are integrated into various parts of the platform to enhance decision-making and optimize operations. These features analyze historical and real-time data to predict delivery times, optimize routing, identify inefficiencies, and proactively detect potential issues. By embedding intelligence into logistics workflows, the platform improves performance, reduces delays, and supports better operational planning for carriers and retailers.
Key capabilities:
- Enhanced prediction and analysis of shipping patterns
- Optimized routing and delivery scheduling
- Automated anomaly detection and reporting
Results & business impact
Scalability and Flexibility
The solution's scalability, flexibility, and cloud architecture reduced maintenance costs and allowed the platform to easily adapt to increasing demand.
Real-Time Tracking
The platform’s real-time tracking system greatly enhanced customer satisfaction and ensured timely deliveries.
Bug Fixing and Feature Enhancements
Our engineers worked proactively to fix critical issues and improve system performance, contributing to faster delivery and a smoother user experience.
Team Expertise Growth
The project helped our team deepen its technical expertise, especially in modern technologies and industry-specific tools, making them well-prepared for future enterprise-level projects.
Customer Satisfaction
The customer was highly satisfied with the results and now views outsourcing as a viable and efficient solution, thanks to our team’s ability to seamlessly integrate into the project and deliver high-quality work.
