AI Image Analysis Dashboard — Real-Time Monitoring System
Client: Japanese Technology Company
The Monitoring Challenge
AI-powered image analysis generates continuous streams of structured data. Without a purpose-built monitoring layer, operators are left parsing raw JSON files manually — a slow, error-prone process that defeats the purpose of having automated analysis in the first place.
Our Japanese client needed a system that could close this gap: taking the raw output of their AI analysis tools and transforming it into an actionable, real-time operational view — with intelligent alerting when results signaled anomalies.
System Architecture
- Java / Spring Boot backend: REST API ingests and processes JSON analysis payloads in real time
- PostgreSQL (AWS RDS): persistent, queryable storage for all analysis results and threshold events
- React.js dashboard: interactive charts, live status panels, and configurable alert views
- AWS EC2 + CloudFront + S3: scalable, globally distributed infrastructure for reliable access
- GitLab CI/CD: automated deployment pipeline maintaining release quality
Key Capabilities
The system delivers three core capabilities: continuous data ingestion (real-time processing of analysis JSON without manual intervention), threshold monitoring (configurable rules that flag anomalies and trigger alerts automatically), and operational dashboarding (a live view of system health and analysis results that operators can use to make decisions instantly).
Delivery & Ongoing Operation
The 18-month engagement (August 2023 – January 2025) included iterative development with regular client reviews, bilingual technical documentation, and a smooth production handover. The system has operated continuously since delivery, providing the client's operations team with a reliable real-time monitoring capability that did not exist before.
Challenge
A Japanese technology company using AI-powered image analysis tools needed a system to ingest, process, and visualize the JSON output data generated by these tools — with automated anomaly detection and configurable alerting when results exceeded defined thresholds. The client required a real-time management dashboard to replace slow, manual review of raw analysis files.
Solution
iPlus Solution designed and delivered a full-stack monitoring system over an 18-month engagement. The backend — built with Java and Spring Boot — exposes a REST API that continuously ingests JSON analysis data, processes it against configurable threshold rules, and stores results in a PostgreSQL database hosted on AWS RDS. The React.js frontend delivers a real-time management dashboard with interactive charts, live status panels, anomaly flagging, and configurable alert notifications. AWS infrastructure (EC2, CloudFront, S3) ensures global availability, low latency, and secure data handling.
Results
Operators gained real-time visibility into AI analysis results for the first time — replacing hours of manual data review with an instant, always-current dashboard. Anomaly detection now triggers alerts automatically, enabling faster response and preventing issues from going unnoticed. The system has operated continuously since delivery without major incidents.
