Projects
Projects
A selection of the most recent projects showcasing full-stack engineering, AI integration, and complex system design.
Key Features
- Advanced filters based on values and categories
- AI-driven models for data categorization
- Machine learning for risk assessment & alerting systems
Results
- 75% reduction in risk assessment processing time
- 40% decrease in false positives
AI-Driven Risk Assessment & Analytics SPA
Challenge
A major financial institution was struggling with manual risk assessment processes that were time-consuming and prone to human error. The client was also looking for quick adaptation to market trends and regulations, and cost optimization.
Solution
Ximplicity implemented an AI-powered risk assessment system that integrated with their existing infrastructure, automating the analysis of customer data and transaction patterns, allowing different workflows and model integration.
Technical Contribution
I designed the data flow architecture to decouple AI inference workloads from the main application, using RabbitMQ for async orchestration between FastAPI model services and the NestJS backend. I built the Angular SPA with dynamic filter pipelines and real-time alerting dashboards, and integrated Keycloak for role-based access across institutional teams. The system was containerized with Docker and deployed on an internal cloud environment with horizontal scaling for inference workers.
Key Features
- Enhanced patient experience
- AI-driven models for agenda optimization
- Automatic rescheduling and quiet messaging
Results
- 40% reduction in patient wait times
- 25% increase in patient throughput
Streamlining Patient Care Workflows
Challenge
A healthcare provider was facing inefficiencies in their patient care workflows, leading to longer wait times and reduced quality of care.
Solution
Ximplicity provided CTO as a Service to analyze their existing systems and implemented a workflow optimization solution that streamlined patient appointments, intakes, diagnosis, and treatment processes without disrupting their systems.
Technical Contribution
I restructured legacy synchronous workflows into an event-driven orchestration model using NestJS and Redis pub/sub, enabling real-time rescheduling without downtime. I designed the React frontend with an agenda-centric UX, integrated TensorFlow-based optimization models via FastAPI, and implemented WhatsApp-style quiet messaging for patient communication. The platform runs on AWS with MongoDB and is secured through Keycloak multi-tenant authentication.
Key Features
- MQTT workflow implementation connected to sensors
- Computer vision integration and machine learning
- Real-time data exchange and business intelligence
Results
- 85% reduction in defect rates
- 60% decrease in quality control costs
AI-Powered Quality Control for Manufacturing
Challenge
A manufacturing company was experiencing high defect rates and quality control issues that were impacting their reputation and bottom line.
Solution
Ximplicity designed and implemented an AI-powered quality control system that used computer vision to detect defects in real time during manufacturing processes, as well as integrated MQTT workflow orchestration into a professional, responsive web application.
Technical Contribution
I designed a low-latency ingestion pipeline that processes sensor and vision data streams via MQTT into a PostgreSQL time-series store, feeding YOLOv12 and Qwen2.5-VL models for defect classification. I built the Angular frontend with live production dashboards, integrated n8n for no-code workflow automation, and exposed an MCP interface for AI-driven process queries. The entire stack was containerized with Docker and orchestrated for edge deployment in factory environments.
Key Features
- Fully integrated digital operation monitoring
- Corrosion models & computer vision analytics
- Symbolic and 3D digital twin inspections
Results
- 90% faster report generation
- Significant cost savings per inspection cycle
NDT Inspections on Refinery Pipelines
Challenge
A robotic NDT inspection provider required a comprehensive inspection portal to preview different NDT data sources over digital twins of inspected pipeline components, and to create automatic annotations and reports based on analytics and computer vision models.
Solution
Ximplicity provided CTO as a Service to structure their business domain, define the data model, and build a web-based solution to manage all data collected by the robot, providing symbolic and digital twin 3D inspection of components.
Technical Contribution
I designed the platform data model to handle heterogeneous inspection sources — RTR (Real-Time Radiography), Pulsed Eddy Current (PEC), and visual — unified under a single schema. I built the Angular + Three.js frontend for 3D digital twin visualization with annotation overlays, developed the SignalR real-time sync layer for collaborative review sessions, and implemented corrosion prediction models in Python. The backend runs on .NET with RabbitMQ for async processing, PostgreSQL and Redis for persistence and caching, and Keycloak for multi-org access control (I authored the data model, technical specification, and integration layer, and developed several core services; other services were built by the extended team).
Beyond implementation as Senior Full-Stack Engineer, I also served as Scrum Master, UX Designer, and Solution Architect on this project. The platform continues to grow in production, and from Ximplicity I remain actively involved in its evolution today — designing and implementing new high-value services, improving the quality, efficiency, and presentation of results, enhancing business processes, and incorporating advanced techniques for data inference, computer vision, and visual information representation within a cutting-edge robotic inspection, analytics, and reporting platform like the one my client delivers to theirs.
Let's Build Something Great
Have a project in mind? I'd love to hear about it and explore how I can help.