I provide end-to-end AI and software engineering services for businesses that need real, production-ready systems — not demos, not experiments.

My focus is building, integrating, and scaling intelligent systems that solve real operational problems and generate measurable business value.

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What I Do

1. Custom AI & Machine Learning Solutions
I design and build AI systems tailored to your business needs, including:
• Computer vision (image analysis, medical imaging, quality inspection)
• Predictive models and classification systems
• Model training, evaluation, and optimisation
• Multi-model inference pipelines
• Explainability (confidence scores, Grad-CAM, overlays)

Models are delivered production-ready, not notebook experiments.

2. AI APIs & Microservices (FastAPI / REST)
I build robust AI APIs that integrate cleanly with your existing systems:
• FastAPI-based inference services
• Secure endpoints (auth, rate limits, logging)
• Batch and real-time processing
• Scalable architecture for cloud or on-prem deployments
• Clean JSON outputs designed for downstream systems

Used in healthcare, CRM platforms, and internal business tools.

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3. Backend Software Engineering
I develop and maintain high-performance backend systems, including:
• REST APIs and service layers
• Database design (SQL Server, PostgreSQL)
• Stored procedures, data pipelines, and reporting logic
• Integration with third-party systems and legacy platforms
• Performance tuning and fault handling

Code is structured, documented, and maintainable.

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4. AI System Integration
I integrate AI into existing products and workflows, including:
• CRM and business platforms
• Internal dashboards and portals
• Referral and queue-based processing systems
• Automated decision and scoring engines
5. Production Deployment & Scaling
I handle the hard parts most developers avoid:
• Model versioning and lifecycle management
• GPU / CPU optimisation
• Environment configuration (Windows, Linux, WSL, cloud)
• Logging, monitoring, and error tracing
• Secure deployment pipelines

Your system runs reliably after handover.

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6. Technical Consulting & Architecture Review
For teams that already have systems in place:
• Codebase reviews
• AI architecture audits
• Performance and cost optimisation
• Data flow and model strategy recommendations
• Clear action plans, not vague advice