Expertise
Data, cloud & applied AI.
iKeeLabs brings together the expertise of its co-founders, Huu Huy Truong and Lorenzo Caraffini, across enterprise architecture, cloud and data platforms, integration and applied AI.
The cloud proficiency levels below are attributed to Huu Huy Truong, as stated in his resume. Other practice areas are presented without a score.
Practice areas
6 areas · 77 topics
- 15 topics
Data & AI Architecture
Enterprise analytics platforms, data lakes, warehousing, master data, quality and governance, with Machine Learning and Deep Learning proofs of concept, model fine-tuning and experiment tracking.
- Enterprise Analytics Platforms
- Data Lakes
- Data Warehousing
- Machine Learning / Deep Learning Proofs of Concept
- PyTorch
- LoRA
- Hugging Face
- spaCy
- MLflow
- W&B
- Data Quality
- Data Governance
- GDPR
- Big Data Architecture
- Master Data Management
- 13 topics
Agentic AI & Enterprise Integration
Agentic AI through an MCP-enabled service hub, enterprise knowledge assistants, retrieval-augmented generation and Azure AI Foundry, together with MuleSoft, event-driven and enterprise-service integration.
- Agentic AI Service Hub
- Enterprise Knowledge Assistants
- Model Context Protocol (MCP)
- LangGraph
- Retrieval-Augmented Generation (RAG)
- Hermes
- Azure AI Foundry
- DSPy
- MuleSoft
- Event-Driven Architecture
- Kafka
- Enterprise Service Bus
- Integration Governance
- 15 topics
Data Platforms & Engineering
Cloud and enterprise data technologies used across the analytics, integration and machine-learning work described in the resume.
- Azure Synapse Analytics
- Azure Databricks
- Apache Spark
- Azure Data Factory
- dbt
- Python
- Airflow
- SSIS
- Power BI
- Qlik
- AWS Athena
- DynamoDB
- Azure SQL Hyperscale
- SQL Server
- Oracle
- 10 topics
Cloud & Platform Architecture
Microsoft Azure — expert in data and solution architecture; advanced in infrastructure and IAM. AWS — proficient in data, analytics and ML solution architecture. GCP — foundational knowledge.
- Microsoft Azure
- AWS
- GCP
- Azure Landing Zones
- AKS
- Red Hat OpenShift
- Kubernetes
- Terraform
- Multi-tenant SaaS Architecture
- Identity and Access Management
- 11 topics
Enterprise & Solution Architecture
Enterprise architecture methods, modelling tools and governance used to produce high-level designs, solution blueprints and architecture-board decisions.
- TOGAF
- ArchiMate
- BizzDesign
- Orbus iServer
- Sparx Enterprise Architect
- UML
- BPMN
- Architecture Review Boards
- Architecture Governance
- High-Level Design
- Solution Blueprints
- 13 topics
Software & Integration Patterns
Application engineering and integration patterns from the .NET delivery years through later API, messaging and DevOps work.
- .NET / .NET Core
- REST APIs
- CQRS
- Event Sourcing
- SAGA
- Microservices
- Message Brokers
- DevOps
- Continuous Integration
- GoF
- MVC
- MVP
- Dependency Injection
Insights
Sourced articles that examine the architecture decisions, controls and trade-offs behind applied AI systems.
- 3 min read
Architecture Decisions: Balancing Cost, Latency and Control
Cost, latency and control pull against each other in every AI system. A useful decision record names the one a use case favors, what it gives up, and the measurement that would reopen the choice. - 3 min read
Where Deterministic Workflows Should Bound AI Agents
An agent earns its place where the path cannot be written down in advance. Authorization, limits, validation and approvals belong in deterministic code around it, so the model works inside a boundary it cannot change. - 3 min read
Why AI Architecture Starts with Evaluation
A component built on a language model has no testable specification until its evaluation exists. Writing the cases and the acceptance bar first turns model, retrieval and prompt choices into measured architecture decisions.