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Fede's AI & Data Lab

AI & Data Lab

Fede Nolasco

Enterprise AI & Data Strategy Leader

Orchestration, Governance & Delivery | Privacy by Design & FinOps

I work at the intersection of data strategy, AI architecture, and operating-model design, helping organisations turn AI interest into a governed portfolio of decisions.

My focus is on deciding where to invest, what evidence to require, which risks and costs to address, and when an AI capability is ready to scale—or should be redesigned, paused, or stopped.

With more than 20 years of experience in regulated enterprise environments, I connect business priorities, data foundations, governance, and delivery teams. I make trade-offs across value, feasibility, risk, economics, and people explicit, then help the right specialists turn evidence into accountable action.

I treat AI as an operating capability rather than a one-time technology deployment. That means establishing workable decision rights, data and control foundations, human oversight, adoption support, and measures that show whether value is actually being realised.

The model is not the product; the operating system around it determines whether value is realised.

Core Competencies

Enterprise AI Strategy AI Operating Models Strategic Delivery Orchestration Product Vision & Roadmaps Architecture Decision-Making AI Governance & Trust Design Privacy by Design Data Readiness & Quality Enterprise Data Architecture AI Economics, FinOps & ROI Workflow & Agentic System Design AI Evaluation & Quality Assurance Human Oversight & Change Enablement Team Coaching & Capability Building Stakeholder Alignment Hybrid Context Architecture Knowledge Graphs Python & Agentic Coding

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Meet Fede in English 1 min intro

This introduction is delivered by an AI avatar, using my own voice. I’m genuinely multilingual and work in English, French, Dutch, and Spanish.

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Key Certificates Credentials in AI, product management, and data science.

Agentic AI Architecture Jun 2026 · Cornell University, eCornell Delivered by Sorin Lerner, Dean; Ayham Boucher, Head of AI Innovations, Cornell Information Technologies (CIT)

Enterprise Product Management Fundamentals May 2026 · Microsoft, Coursera Delivered by Marni Baker-Stein, Chief Content Officer

The Data Scientist’s Toolbox Feb 2016 · Johns Hopkins University, Coursera Delivered by Jeff Leek, PhD; Roger Peng, PhD; Brian Caffo, PhD — Department of Biostatistics

20+

Years Experience

EU AI ActGDPR

AI Governance & Privacy by Design

DORANIS2

Operational Resilience & Security

ISO 42010

Enterprise Architecture Discipline

Career Timeline

Where I Worked

A track record of designing and delivering enterprise-grade data & AI solutions across highly regulated sectors.

Zoetis

Current

August 2021 — Present | Lead, Data and Platform Architecture

Enterprise Architecture & Governance: Guide internal platform consumers on optimal data architecture patterns, ensuring robust compliance through strict adherence to Data Privacy by Design and Application Rationalization.

Applied AI & Productivity: Proactively identified operational bottlenecks and engineered custom AI productivity solutions using Task Decomposition to accelerate Power BI Semantic Models and generate self-service DAX metrics for FinOps.

Autonomous Workflows: Designed and deployed agentic systems utilizing Specification Precision to automatically map internal business capabilities against the APQC classification system.

Process Automation: Created specialized AI agents to streamline internal communications and automate team deliverable reporting, converting complex manual processes into efficient autonomous AI-driven systems.

Cloud & Platform Optimization: Oversee the expansion of Databricks partner capabilities while architecting Artificial Capable Intelligent Systems engineered for autonomous FinOps insights and cloud cost optimization.

Enterprise Architecture Task Decomposition Specification Precision Agentic Workflows Power BI FinOps Databricks

Datatunnel

March 2018 — August 2021 | Solutions Architect & Founder

Operated as a fractional Data & Solutions Architect, advising enterprise clients on modern data strategies, analytics roadmaps, and advanced BI implementations.

Architected and engineered end-to-end data lake and data warehousing solutions leveraging Azure Cloud, SQL, and Python/R analytics.

Transitioned clients away from poor legacy data practices by implementing strict Data Governance principles and establishing scalable organizational processes.

Designed and deployed production-grade BI platforms and dashboard visualizations to enhance advanced analytics insights for leadership teams.

Data Strategy Azure Cloud Data Lake Architecture Data Governance BI Platforms Python / R

Dept of Justice and Equality

October 2015 — October 2020 | Solutions Architect

Enterprise Data Governance & GDPR: Developed enterprise-wide data capabilities and established rigorous governance best practices, playing a critical role in driving structural changes for GDPR compliance across the department.

Infrastructure Modernization: Architected and modernized the analytics infrastructure for the Research and Data Analytics (RDA) division, delivering highly optimized reporting solutions that achieved a 90% reduction in processing time.

Advanced Analytics & Prototyping: Spearheaded technology prototypes within a secure government environment, integrating R as the core data analysis infrastructure and deploying the ELK stack for widespread government adoption.

Strategic Capacity Building: Strengthened the core data analysis capabilities of the Irish National Immigration Services (INIS), translating complex legacy data into actionable, secure intelligence.

GDPR Compliance Data Governance Infrastructure Modernisation ELK Stack 90% Faster Reporting Public Sector

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What I Am Interested In

Enterprise AI succeeds when strategy, architecture, and economics are designed together. I help organizations identify the right AI opportunities, ground them in trusted data through Hybrid Context Architecture, and make them sustainable through Token Economics, governance, and clear autonomy boundaries. My role is to translate business ambition into practical AI systems that are useful, auditable, and cost-aware.

Target AI Domains

Enterprise AI Strategy AI Opportunity Selection Data Readiness & Quality Hybrid Context Architecture Agentic Workflow Architecture LLM Evaluation & Quality AI Governance & Trust Design Responsible Autonomy Boundaries Cost & Token Economics Legacy-to-AI Modernization

Industry Focus

Life Sciences & Pharma Healthcare Public Sector Financial Services Insurance Supply Chain & Manufacturing Energy & Utilities Retail & Consumer

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Fede Nolasco

AI Architecture Guidance

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Open to consulting, advisory, and full-time opportunities

Architectural Thinking

Agentic Economy

Moving beyond "Agent-as-a-Chatbot" to "Agent-as-Infrastructure."

Architectural Philosophy

In the Agentic Economy, the bottleneck is no longer model intelligence, but the quality of context and the ROI of token burn.

Principal Concepts & Frameworks

Hybrid Context Architecture vs. Vector RAG

Moving from semantic similarity to structural traversal. Combining knowledge graphs with agentic reasoning to give systems a "Map" of context rather than a flat "List" of facts.

Hierarchical Conductor Models

Implementing Supervisor LLMs to manage specialized sub-agents, ensuring vertical accountability and reducing task drift.

Token Burn & ROI Economics

Applying cost-modeling to determine where multi-agent reasoning justifies token expense versus where deterministic code suffices.

The "Infer vs. Know" Paradigm

Using Knowledge Graphs to make retrieval deterministic, mitigating hallucinations in highly regulated environments (Pharma/Government).

The Architect's Manifesto

"The true value in the Agentic Economy is not the agent itself, but the clarity of the specification and the robustness of the harness that contains it. We are not just building tools; we are architecting the logic of the modern enterprise."

Agentic Pillars

Hybrid Context Architecture Conductor Architectures Token Arbitrage Inference Guardrails Agentic Observability Multi-Agent Coordination