Selected case studies

A short selection of work across cloud migration, security operations, automation, identity integration and product delivery. Some enterprise examples are anonymized to avoid exposing client-sensitive information.

Cloud migration and infrastructure modernization

Context

Enterprise environments required support moving from VMware and legacy infrastructure toward Azure, GCP, private cloud and hybrid models.

What I worked on

Planned migration work, coordinated VMware-to-cloud activity, checked SD-WAN/cloud connectivity, aligned suppliers, compared cloud costs, tracked risks and dependencies, handled technical troubleshooting and prepared cutover steps.

Outcome

Improved migration structure, clarified dependencies, strengthened supplier coordination, improved risk visibility and made the transition from legacy infrastructure to cloud services more controlled.

Technologies

VMware
Azure
GCP
private cloud
SD-WAN
Cisco
Windows
Linux
MS SQL

Security operations and SIEM/XDR onboarding

Context

A distributed global environment needed support integrating security platforms across on-premises and cloud sites.

What I worked on

Onboarded Bitdefender XDR and IBM QRadar data sources, validated connectors, checked firewall paths and log transport, and prepared operational guidance for local IT teams.

Outcome

Reduced onboarding friction and gave local teams clearer checklists, escalation points and technical instructions.

Technologies

Bitdefender XDR
IBM QRadar
Azure
SD-WAN
MPLS
firewall paths
log transport

Patching and vulnerability process redesign

Context

Critical infrastructure teams needed a more repeatable Windows patching and vulnerability management process after a major security incident.

What I worked on

Redesigned operating procedures with Ansible, helped move work from SCCM to Ansible, built RACI documentation, updated runbooks and trained junior staff to operate the process.

Outcome

More standardized operations, clearer responsibilities and a process that could be handed over and repeated by the team.

Technologies

Windows Server
Ansible
SCCM
PowerShell
RACI
runbooks

IAM integration and technical delivery management

Context

A multinational IAM environment required support across Oracle HCM/RIS, Microsoft Entra ID and connected identity flows, including technical integration plus delivery management around validation, evidence, vendor follow-up, stakeholder updates and production readiness.

What I worked on

Worked on IAM workstream management, scripted REST integration, deterministic mappings, filtering, normalization, monitoring scripts, validation evidence, Microsoft Entra ID safeguards, vendor coordination, ticket ownership, stakeholder updates, risk and dependency tracking, production runbooks, Go/No-Go gates and handover notes.

Outcome

Improved stability and auditability of identity flows, clearer validation evidence, better production handover and stronger management of tickets, risks, stakeholders and vendors across the IAM workstream.

Technologies

Oracle HCM/RIS
Microsoft Entra ID
IAM delivery management
ticket ownership
validation evidence
Go/No-Go support
Bash
Python
Microsoft Graph API
JSON

Eventario — founder-built App Store product with lean AI workflows

Eventario website Apple App Store

Context

Eventario is an independently built iPhone app for discovering local events in Italy, published on the Apple App Store. The product helps people find concerts, festivals, nightlife, food markets, exhibitions, sport events and local experiences, with discovery based on mood, interests, location and lifestyle.

What I worked on

Product positioning, mobile UX direction, event discovery flows, search and filters, privacy/legal preparation, App Store release, iteration and AI-assisted development workflows.

Outcome

A real consumer product shipped to the App Store, showing end-to-end product ownership and the ability to combine product thinking, AI-assisted workflows, cost control and production release discipline.

AI chain and cost-aware product design

The product direction is built around a lean AI chain: collect event information, normalize it, enrich it with categories and mood/context tags, use structured outputs where possible, store reusable enrichment, and combine deterministic filters with recommendation logic. The goal is not to call an expensive model for every user action, but to use AI where it adds value and keep the product lightweight enough to operate at an early-stage budget.

Event intake and normalization from fragmented event information.
AI-assisted enrichment for categories, moods, atmosphere, audience and tags.
Structured event data that can be reused instead of regenerated.
Recommendation logic based on mood, interests, location and event context.
Connecting users around shared interests, saved events and attendance intent.
Cost control through batching, caching, deterministic filtering and human review.
Higher-cost AI only where needed, not for every page view or simple filter.

Technologies

mobile app
event discovery
location-aware search
structured event enrichment
recommendation logic
privacy/legal flows
App Store release
AI-assisted development workflow

Need technical support on a project?

For consulting help, send a short note about the project and where support would make the work easier to move forward. I am also open to product and automation work where AI can reduce manual effort without creating unnecessary operating cost.

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