Question 1

What does "AI Specialist & Enterprise Architect" mean in practice?

Accepted Answer

Two-handed work: on one hand, GenAI / agents / RAG patterns and the LLM stack; on the other, the enterprise-architecture discipline (TOGAF, ArchiMate, integration, security) that makes those patterns survive an audit. Most clients hire one and then discover they need the other — I bring both.

Question 2

Why bring AI into a payments or regulated business?

Accepted Answer

Because the ROI on internal AI (developer productivity, documentation, support, compliance evidence) is already provable, and because the regulatory window — PSD2, DORA, GDPR, AI Act — closes on whoever waits. The goal is governed adoption, not a press release.

Question 3

How do you keep AI compliant with PSD2, DORA, GDPR and PCI-DSS?

Accepted Answer

An AI-governance framework: LLM gateway, audit logging, guardrails, prompt / response retention rules, vendor inventory, and each control mapped to a monitoring pillar. The same posture I designed inside a payment group is what I bring to clients.

Question 4

What's the difference between Light, Medium and Intensive?

Accepted Answer

Light is a 1–2 week independent second opinion. Medium is a 4–8 week governance & roadmap engagement. Intensive is a 2–3 month build that graduates a real use case under guardrails. Same person, different sizes.

Question 5

Which AI stacks do you work with?

Accepted Answer

Anthropic Claude (including Claude Platform and MCP), OpenAI, Azure AI, Google Vertex AI, Ollama for on-prem; ChromaDB and LangChain for RAG. Python and Java on the back end, AWS / GCP / Azure for deployment.

Question 6

How fast can we ship a first GenAI use case?

Accepted Answer

Internal tooling and RAG over your own documents can be in pilot in 4–8 weeks if you have a clear sponsor and a single use case. Agent-based workflows take longer because the guardrails and evaluation matter more than the model.

Question 7

Can you work alongside my existing architecture or AI team?

Accepted Answer

That is the typical engagement shape. I plug in as the fractional senior — architecture, governance, second opinion — and your team owns delivery. Knowledge transfer is built into every package.

Question 8

How is Hawk Nest different from a big consulting firm?

Accepted Answer

No pyramid, no junior partners doing the work. You get me, with 25+ years of payment-systems experience and a track record of enterprise architecture inside the industry. Engagements are small, written, and senior-led from end to end.

Question 9

How do banks adopt GenAI without breaking core payment systems?

Accepted Answer

By keeping AI as a governed layer above the core, never inside the authorization path. GenAI handles knowledge, drafting, triage and developer productivity, while ISO 8583 / EMV transaction flows stay untouched and deterministic. Every model call passes through an LLM gateway with audit logging, guardrails and retention rules, so adoption is incremental and reversible.

Question 10

What does a fractional AI architect / Enterprise Architect do?

Accepted Answer

A fractional AI / Enterprise Architect gives a regulated business senior architecture leadership part-time, without a full-time hire. The work spans two disciplines: the GenAI stack (agents, RAG, LLM gateways, evaluation) and the enterprise architecture (TOGAF, ArchiMate, integration, security) that makes those patterns survive an audit. Engagements run from a 1–2 week second opinion to a 2–3 month build, paid by outcome rather than headcount.

Question 11

How do PSD2 and DORA affect AI deployments in financial services?

Accepted Answer

PSD2 frames strong customer authentication and third-party access, so any AI touching payment or account data inherits those controls. DORA adds operational-resilience duties — ICT risk management, incident reporting and oversight of third-party providers, which now includes LLM and cloud-AI vendors. In practice that means a vendor inventory, documented controls, audit logging and an exit plan for every AI dependency, with GDPR and the EU AI Act layered on top.

Question 12

What's the difference between an AI pilot and production-grade GenAI?

Accepted Answer

A pilot proves a model can do something interesting in a demo; production-grade GenAI proves it can do it safely, repeatably and under audit. The gap is everything in between: evaluation, guardrails, access control, observability, cost controls, retention policy and a run-book for when it misbehaves. Most failed AI programmes die in this gap because no one owned the architecture — graduating one real use case under guardrails is exactly what an Intensive engagement delivers.

Question 13

When should a company hire fractional vs. full-time AI leadership?

Accepted Answer

Hire fractional when you need senior AI and architecture decisions now but don't yet have enough steady-state work — or budget certainty — to justify a permanent executive. A fractional architect sets direction, governance and the first production use case, then hands a run-book to your team. Move to full-time once AI becomes a continuous core function with a team to lead; many clients use a fractional engagement to de-risk and scope that eventual hire.

AI withoutbreaking what already works.

AI Specialist & Enterprise Architect for Financial Services & Payments.

Welcome AI

AI governance framework

Agent-based PoCs

FAROL-SI RAG platform

What I do

Fractional AI Strategy & Advisory

Architecture as a Service

Hands-on GenAI Implementation

Independent Second Opinion

Packaged engagements

Light

Medium

Intensive

How an engagement runs

Discovery call

Framing

Delivery

Handover

Frequently asked questions