Leadership
Douglas Guncet
Cloud & AI Architect | Enterprise Modernization | Microsoft Azure | Agentic Systems
“AI is most valuable when it becomes part of the actual workflow.”
Douglas works at the intersection of enterprise architecture, Microsoft Azure, application modernization and applied artificial intelligence.
His work focuses on moving AI beyond experimentation and integrating intelligent capabilities into real applications, workflows, cloud platforms and operational systems.
His experience spans enterprise cloud architecture, application modernization, infrastructure, software engineering, DevOps, AI agents, intelligent automation and AI-assisted development.
His current areas of focus include AI enablement, enterprise modernization, agentic systems and understanding how intelligent agents can coordinate work across software systems and people while maintaining appropriate human oversight.
His hands-on work and experimentation span multiple operational domains, including enterprise modernization, document intelligence, insurance compliance, real estate operations, workflow automation and modern application development.
Microsoft Ecosystem Expertise
Our engineering and architecture work is centred on the Microsoft cloud platform and its AI, application and DevOps services.
- Microsoft Azure
- Azure Landing Zones
- Azure AI Foundry
- Azure OpenAI
- Azure App Service
- Azure Functions
- Azure Kubernetes Service
- Azure API Management
- Azure SQL
- Azure Key Vault
- Azure Monitor
- Microsoft Entra ID
- GitHub
- GitHub Copilot
- Azure DevOps
- Bicep & Terraform
Writing
Articles by Douglas
Azure Landing Zones in the AI era
How enterprise Azure architecture — identity, networking, policy, observability and cost control — evolves when AI applications and agents enter the estate.
Read the articleAgent governance: who is responsible when AI can act?
Identity, authorization, approval gates, observability and cost control for AI systems that do not just answer questions but take action in enterprise systems.
Read the articleLegacy modernization sequencing
A practical framework for deciding what to stabilize, expose and modernize before introducing AI — and what does not need a rewrite at all.
Read the articleThe human follow-up gap
Enterprise software records requests and results well. People perform the coordination in between. That gap is the largest practical opportunity for AI agents.
Read the articleFrom document intelligence to action
Extracting fields from documents is a solved-enough problem. Turning extracted information into validated, reconciled, actioned outcomes is where the value is.
Read the articleThe AI modernization factory
How human architects, specialized agents and orchestration combine into a repeatable modernization capability across an application portfolio.
Read the article
Applied work
Case studies and internal innovation
Multi-Application Azure Modernization with AI Agents
Using orchestrated AI agents to accelerate application discovery, architecture analysis, modernization and Azure deployment
Read the case studyAI-Enabled Insurance Compliance and Certificate Management
Turning insurance documents into actionable operational intelligence
Read the case studyAgentic Property Operations and Work Order Automation
Closing the operational gap between creating a work order and actually completing the work
Read the case studyAI-Assisted Competition and Event Operations Platform
Turning domain expertise into a real-time operational application
Read the case study