Enterprise Projects

Systems I’ve designed and delivered.

Six enterprise AI and data projects across financial services, healthcare, and fintech — each with architecture diagrams, tech stack, and measurable business impact. These are production systems, not demos.

Production systems

$16M+

Business impact

Cloud platforms

18yr

Enterprise experience

Enterprise AI

Vendor Intelligence Automation

RAG-based intelligent chatbot with multi-layer architecture: SharePoint ingestion, vector embedding, graph retrieval engine with intelligent router for hybrid query handling (structured + semantic search). Event-driven automation via Power Automate for multi-channel communications.

$3M+

Annual savings

+85%

Decision speed

PythonAzureReactLangChain+3 more

Enterprise AI

Document Intelligence Platform

Secure enterprise document intelligence chatbot built on Google Cloud. Multi-tenant architecture with knowledge graph (Neo4j) for relationship mapping across document corpus. Improved onboarding speed and compliance across geographies.

-60%

Onboarding time

Significant

FTE savings

PythonLangChainOpenAIDocument AI+3 more

Finance Automation

Invoice Intelligence Platform

Multi-cloud invoice extraction pipeline: secure authentication via Workload Identity Federation + Graph API, Document AI processing with business rules engine, automated synchronisation to BigQuery. Replaced a fully manual process that took days per cycle.

+40%

Accuracy improvement

-70%

Manual effort reduction

$1.5M

Annual savings

PythonGCPReactGemini Flash+4 more

Healthcare

GenAI Rule Platform — US Healthcare

GenAI-powered Rule Engine automating policy logic creation and medical reviews. Used FlanT5 for text understanding, AWS Textract for document parsing, and a custom rule engine that translates natural language policies into executable business rules.

-90%

Cycle time reduction

+70%

Efficiency improvement

AWSReactFlanT5 ModelTextract+2 more

Fintech SaaS

Recommendation Engine — Fintech SaaS

Enterprise SaaS Recommendation Engine for banking clients. Managed end-to-end delivery: API design, data governance, model orchestration with decision trees and collaborative filtering, and deployment patterns across 7+ banking implementations.

AED 4M+

Revenue generated

+20%

Client retention

PythonAWSDecision TreeCollaborative Filtering+2 more

B2C Fintech

ML Lending Platform — B2C Fintech

ML-powered underwriting platform using decision trees, gradient boosting, and logistic regression. Managed 60+ person cross-functional team across engineering, data science, and operations. Built model monitoring, A/B testing framework, and continuous improvement pipelines.

-20%

Default rate reduction

-35%

Post-launch issues

+25%

Feature adoption

PythonScikit-LearnGradient BoostLogistic Regression+2 more

Interested in working together?

Open to enterprise AI architecture roles — particularly in the Netherlands and Germany.

Get in touch →Download CV ↓