Alireza Chegini

Enterprise AI architect. Production-grade, governance-aware, built for regulated environments.

Most generative AI stops at the demo. The systems I build are the ones that have to keep working: under production load, under audit, under scale that doesn't forgive shortcuts.

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About

I'm an enterprise AI architect with 25+ years in software engineering, cloud, and large-scale digital transformation. For the last several years I've designed and delivered production-grade Generative AI, including RAG, agentic systems, AI platforms, and the governance layers around them, inside demanding, regulated environments where a system has to be safe, auditable, and correct, not just impressive in a demo.

I founded and led an enterprise GenAI platform inside a regulated, financial-grade environment — architecture through governance, security review, and production operations. Most people advising on this have never had to get one past an audit.

My edge is judgment and proof. I've shipped enterprise AI under real constraints of compliance, risk, cost, scale, and organizational reality, so I know where these systems break and what it takes to keep them standing. As the EU AI Act's high-risk requirements land, the gap between a working demo and a defensible production system is exactly where the hardest, most valuable problems live.

That's the work I do.

What I believe

Strategy is not a substitute for a working system.

"Agent" means four different things. Knowing which one you mean is the difference between a roadmap and a wish.

I build the hyped thing myself before I trust it, so I can tell you where it breaks.

A demo proves it can work once. Production proves it works when it has to.

Work with me

A programme for the people who have to make the decisions.

Four modules on the parts of enterprise AI that decide whether a system survives contact with production, an audit, and scale. Take the whole programme, or a single module.

Module 01

What “agent” actually means

One word covering four different architectures, with different costs, failure modes and governance burdens. Which one your problem actually needs — and how to recognise the cases where the answer is none of them.

Module 02

Agentic architecture in practice

Orchestration, tool use, memory, and what happens when a step fails halfway through. The patterns that hold up, the ones that quietly do not, and the operational cost of each before you commit to it.

Module 03

Retrieval that survives production

Why retrieval systems that demo beautifully degrade in production, how to evaluate one honestly, where the cost actually accumulates, and what to measure so you find out before your users do.

Module 04

Building for the AI Act

Risk classification as an architectural decision rather than a form. Human oversight as something you build, not someone you add. What traceability requires of a system that was not designed for it.

Run against your own architecture and constraints — not generic examples.

FormatHalf-day to two-day modules, on-site or remote

ForArchitecture, platform and engineering leadership

You keepSlides, a patterns reference, and the decision criteria

Scope & pricingOn request

Not sure which modules fit, or want something the programme does not cover? Tell me what you are trying to get right and I will tell you honestly whether I am the right person for it.

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Proof

Platform

An enterprise GenAI platform, in production, under audit

Founded and led an enterprise Generative AI platform inside a regulated, financial-grade environment: the architecture, the governance and responsible-AI layers, the security review, and the operational reality of running it once real teams depend on it. Client work is confidential, so I describe it in general terms — but it is the reason I can tell you what will break before it becomes expensive.

Open, public

The Living AI Atlas

A free, open map of AI — what these systems do, how to use them, and how to judge what they hand back. Plain language, no paywall, no account, no sponsorship. It is maintained rather than published once, with a last-revised date on every page and corrections made in the open. You can read it and judge the standard of my work without signing anything.

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Writing

Architecting AI

Essays for people who have to make these decisions rather than admire them — on the AI Act as an architecture problem, on why strategy decks replace working systems, and on what actually fails between a pilot and production. Where I build the hyped thing myself first, I say where it broke.

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Selected writing · Architecting AI