AI Delivery
Permission-Aware RAG: Propagating ACLs into a Vector Index
Why filtering RAG results by ACL collapses recall to 39.7%, how Jira and Confluence permissions really resolve, and the three architectures that survive audit.
Enterprise Data & AI Leadership
Emanuel Mallia
Leading enterprise Data & AI mandates from strategy through production.
Data platforms, governance and AI systems built for regulated businesses in fintech, telecoms, iGaming and payments.
Key Achievements
Enterprise Data & AI Mandate
Strategy, governance, platform and delivery under one owner.
4 Functions Led
Data engineering, databases, analytics and AI.
Adopted As Gold Standard
The delivery approach the business standardised on.
Regulated Markets
Fintech, telecoms, iGaming and payments.
Expertise
End-to-end delivery, from data infrastructure to the AI layer that sits on top.
View expertiseData & Database Architecture
Database selection, warehouse and lakehouse design, real-time pipelines, and the analytics layer that sits on top. Built for scale and query performance.
AI Delivery & Integration
AI agents, RAG pipelines, multi-agent systems, LLM integration, and MCP, built on solid data foundations. Production systems that run past the proof-of-concept.
Technical Leadership
Data strategy, team building, and hands-on delivery. Turning technical complexity into outcomes the business can act on.
Working stack
- Databases & warehousing
- PostgreSQL
- MySQL
- Oracle
- SQL Server
- MongoDB
- Elasticsearch
- AWS Redshift
- Snowflake
- Pipelines & streaming
- Apache Airflow
- dbt
- Apache Spark
- Apache Kafka
- Real-time Pipelines
- Data Mesh
- ELK Stack
- Platform & observability
- Kubernetes
- Docker
- Terraform
- Ansible
- Python
- DataDog
- Grafana
- Prometheus
- AI systems
- Anthropic Claude
- LLMs
- AI Agents
- Multi-Agent Systems
- RAG Pipelines
- MCP
- Vector DBs
- LangChain
- MLOps
Working systems over presentations.
Production over proof of concept. From data architecture to AI delivery, the bar is what ships.
Latest Insights
Thoughts on AI delivery, data architecture, and technical leadership.
Start the Conversation
From data architecture to AI delivery, with a focus on execution, scale, and production readiness.