Marciano Hardjowikromo · Technical AI Implementation Partner · Groningen, NL
80% of AI projects never reach production. I build the 20%.
From prototype to production — with everything that comes with it: evals, guardrails, monitoring, governance and SLAs. AI that demonstrably contributes to your P&L. 20+ years of engineering, working within a week — not quarters.
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From demo to running system — the real work starts after the prototype
An impressive demo is built in an afternoon. Production is the real work: secure, monitored, integrated and demonstrably profitable. That entire journey is what I deliver — hands-on, no thick reports, with a system that runs when I leave.
- Production-ready from day one — evals, guardrails, monitoring and SLAs, no demo-ware.
- Working within a week — delivery on Monday, so your team starts the week testing.
- Vendor-independent — Claude, Mistral, Llama, Qwen or Gemma: the right model for your use case and budget.
- Cloud or on-premise — GDPR and AI Act-proof, locally hosted when data sovereignty matters.
- Seamless integration — ERP, PIM, CRM and your existing processes.
The 20 pressing AI questions in business
These are the questions I see on boardroom tables every day — with extra weight on data sovereignty, local hosting and European regulation. With 20+ years of engineering, working daily with Claude, Gemini, Codex and Grok (xAI), I translate them into answers that run.
I. ROI & strategy
What will AI demonstrably deliver — and when?
I start with the business case: which processes cost time or money today, what the savings are and when you break even. Measured from week one.
Which ecosystem do we choose — Microsoft 365 Copilot or open source?
Switch on Copilot or build a flexible open-source layer? I benchmark both on your use case and prevent vendor lock-in.
Build, buy or wait for our software vendor?
Your own AI layer, or wait until AFAS, SAP or your PIM ships AI? I run the numbers on both scenarios — including lock-in and exit costs.
II. From prototype to production
Why do 80% of AI projects fail — and ours won't?
Pilots fail on data, integration and ownership, rarely on the model. I build from day one with evals, monitoring and an owner per process.
How does our ChatGPT/Claude prototype become a production system?
From sandbox to hundreds of users: LLMOps, scalability, monitoring and SLAs.
How do we safely connect AI to ERP and CRM?
Reliable APIs and RAG pipelines with live access to your existing systems — with permissions and logging.
Is our data infrastructure ready for AI?
Garbage in, garbage out. I help make folders, sheets and mailboxes AI-ready before we build.
How do we test whether the AI is good enough for customers?
Eval sets with real cases and a clear bar per release: only live when the numbers say so.
III. Sovereignty, data & EU regulation
How do we guarantee our data never leaves the EU?
Sovereign cloud guarantees and EU data centers — locked down technically and contractually.
Can we run AI fully on-premise or in a private cloud?
Llama or Mistral on your own servers, even without an internet connection. This is my specialty.
Does our AI application count as 'high-risk' under the EU AI Act?
I assess your system against the AI Act and set up compliance and transparency pragmatically — before the regulator asks.
How do we keep foreign governments (CLOUD Act) out of our data?
US cloud in the EU isn't enough. I arrange legal-technical shielding.
IV. Quality, costs & risks
Who is liable when the AI makes a critical mistake?
I design processes with human-in-the-loop and clear responsibility per decision.
How do we prevent hallucinations reaching customers?
Automated guardrails, evals and observability — measuring instead of hoping.
What does this cost us monthly (FinOps)?
Token budgets, caching and the right model per task keep costs predictable — accounted per use case.
Who owns the intellectual property of AI output?
Design, code or contract: I advise on protecting and licensing output.
V. People, organisation & adoption
How do we deal with 'shadow AI' on the work floor?
Employees already use free ChatGPT. I channel that into a safe business environment.
How do we get employees to actually use it?
Training, prompt skills and taking away fear — adoption is change management.
Can our team manage it themselves afterwards?
Documentation, runbooks and handover are part of the delivery. You don't depend on me — unless you want to.
How do we prevent our solution being outdated in two years?
Model-agnostic architecture: swap LLMs tomorrow without rebuilding.
Why companies call me
No technology for technology's sake — four business problems I run into daily, and the AI solution that already solves them today.
Microsoft 365 Copilot & Azure AI
You're already paying for Copilot licences, but the returns aren't showing up. I handle the readiness, governance and data integration that's missing — so Microsoft 365 Copilot & Azure AI finally deliver what you're paying for.
Sovereign AI & local hosting
Your data can't just go to a US cloud, and that clashes with the AI Act. I deploy open-source models on-premise or in the EU: full control, GDPR and AI Act compliant, without giving up capability.
AI knowledge assistants (RAG)
Employees and customers waste hours digging through folders, manuals and old emails. An AI knowledge assistant (RAG) answers those questions instantly — up to 78% less support load.
AI agents & process automation
Quotes, email and order processing eat hours you don't have. AI agents take over the repetitive work — with a human in the loop where it matters — turning days of work into minutes.
Results from production
−78% support load, thanks to a knowledge assistant (RAG + observability).
+89% on-site conversion through better recall, ranking and vector search.
−69% lead time through automated decisioning and CI/CD for ML.
Translations I've made before
Bobbette — Quote chatbot
Sales assistant that structures quote requests and suggests pricing. Azure OpenAI, private data, RBAC.
ProFlights — Flight deal finder
AI flight comparator that detects price drops and tells you when to book.
AI Blogwriter — Automated content
Content pipeline that writes, publishes and shares AI news daily via X — hands-free.
My 6~7 Brain — Second brain
Privacy-first iOS app as your second brain: capture, search and connect — fully on-device.
Domain Bidder — Domain auctions
Auction platform for premium domains: bids, Stripe payments and transfer, fully automated.
Mailbox Jungle — Smart inbox
Unified inbox with AI rules, templates and campaigns. Gmail, Outlook, IMAP and more.
Lent — Lending tracker
Mobile-only app to track what you've lent out and to whom. No web dashboard — just the iOS/Android app, syncing securely in the background via mhard.ai SSO.
TailorFitWMS — Warehouse Management
Op maat gebouwd magazijnsysteem voor Cookinglife: order-intake, picking, voorraad en NetSuite ERP-synchronisatie, bijna twee jaar in productie.
CarrierAPI — Multi-carrier verzendplatform
Self-hosted alternatief voor SendCloud: één API voor labels, tarieven en tracking over meerdere vervoerders, met NetSuite- en Shopify-koppeling.
Multi-tenant PIM-platform
Productdata centraliseren, verrijken met AI en synchroon houden over Shopify, marketplaces en ERP — met een ingebouwde RAG-assistent en een mens die elke wijziging controleert.
Multi-tenant PIM-platform
AI-verrijking, Shopify-first sync en multichannel export naar marketplaces, met een ingebouwde RAG-assistent voor het productteam.
See my live AI tools at mhard.ai →
AI in the Northern Netherlands
I work from Groningen for companies across the Northern Netherlands — Groningen, Friesland and Drenthe. On-site at the table when needed, remote when possible. And beyond: all of the Netherlands and the EU.
// Groningen · online · response < 24h