Process-first AI consulting

Do you know where AI would actually save your team time?

Most teams can't answer that question, and that's exactly where AI rollouts fail. We start where your work actually happens. The queue that backs up. The edge cases your team handles by hand. The tool your people actually use. Standard packages when the use case fits, custom builds when it doesn't.

Three ways in

What we do.

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Services
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EN/NL
Languages Spoken

Consultancy

We stop the expensive guessing.

We show you exactly which AI use-cases will move the needle in your business and which ones won't.

You walk away with a clear strategy, prioritized use-cases, vendor shortlist, and a realistic rollout plan so you only invest where it actually pays off.

Implementations

We build AI that your team actually uses and your customers feel.

From customer-facing chatbots and internal agents to complete automated workflows, always designed to fit the way you already work.

Result: less manual work, faster responses, and systems that keep improving instead of collecting dust.

CerAImic Nerve Center

Your AI-powered operations layer that delivers services directly to your customers.

Web design, ticket handling, custom integrations, and more, running continuously while you stay in control.

Think of it as the always-on team that never sleeps, never forgets context, and keeps getting better at serving you or your clients.

The difference

What we do instead.

Most AI consultancies sell you a tool somebody else built. CerAImic built its own, ran the firm on it, and advises from what that taught us.

The consultancy model: recommending what somebody else built

  • Most AI consultancy firms are not really consulting.

    They resell ready-made blocks of service, mixed and linked together. They have not had the hard, deep talks about what you actually do. A block can look close to how a standard workflow runs, but does that fit how you work?

  • Nobody in the firm runs what they recommend.

    Most AI resellers have never been customer 0. They have not built what they recommend and have not lived with it, so they know the demo, not the edge cases that turn up in month two. They have never looked at their own company the way they would look at a client's, and built there what they would have advised you to do. We call this eating your own dogfood. How would you feel if the CEO of a plane manufacturer did not want to fly in the planes they were making?

  • The advice stops at the recommendation.

    A deck, a pilot, a licence. Once it is signed the firm has no way of knowing whether it worked, so there is no pressure to go and find out.

  • You inherit somebody else's dependency.

    The recommendation routes your work through a vendor's platform, and every hour you run it is an hour you could not take somewhere else.

CerAImic: built it first, then ran the firm on it.

  • CerAImic started as one person learning AI, not selling it.

    Models, agents, workflows. The practice grew out of building and reading rather than out of a partner programme, so there is no reselling layer between what we recommend and what we made.

  • The Nerve Center was internal before it was ever an offer.

    It was built to run CerAImic and our own projects, not to be sold. The framework got some attention and people asked to buy it, but it is made for how we work, so we decided we did not want to turn it into a product. Instead we run proofs of concept. People tell us the problem they want solved, and we look at whether the framework can handle it or needs building for it. That is how it slowly grew into something that faces outward.

  • It does the real work of the firm, every day.

    It reads our email and messages, plans appointments, keeps priorities straight, researches what the best consultancy advice and the best implementation path even are, and tells us what is next when we are not sure.

  • So the advice comes from someone already living with it.

    When we recommend a model or a method it is because we have run it on our own work and know where it breaks. That is the whole difference dogfooding is supposed to make.

The flagship

The CerAImic Nerve Center.

It started as the tool we run CerAImic on, and it is now what we offer clients. It is an AI-centric system that delivers services to your customers.

What does the CerAImic Nerve Center Framework currently do?

Web design

Modern, fast websites with AI-native architecture. Built to load fast and actually work.

Ticket handling

Triage, response drafting, and escalation routing. Handled faster, with fewer edge cases slipping through.

Custom connectors

API integrations, data pipelines, and middleware built for your specific stack and use case.

What have we shipped using the CerAImic Nerve Center.

Built for customers, end to end.

CerAImic has shipped dozens of applications for customers, from initial ideas to customers' preferred hosting platform of choice.

CerAImic has POCs, and has shipped several consumer services, ranging from Divorce Co-Parenting to a neuro-linguistic programming audit platform where couples can analyse what is going on when they argue.

Who builds CerAImic.

CerAImic is built by Ali Najef Abu Ita, Technical ITAM consultant at Noventiq. CerAImic is a one-person practice. Founder availability is the bottleneck. If you need a 24/7 staffed service desk or an always-on team, you'll need to go with one of the more expensive agencies.

CerAImic is an independent practice. Not affiliated with Noventiq, Flexera, Snow Software, or Octopus.

A small selection

Who we work(ed) with.

CerAImic is a young company. We currently focus on small to medium companies.

CerAImic was created in 2025. It started as a side project but is slowly taking shape in something more.

Security officer on patrol

Security Firm

Working dog in harness

Dog Security

Person wearing an identity badge on a lanyard

German IDP company

Teacher helping a student at a desk

Private school

Salon interior with chairs and mirrors

Hair/nail salon chain

and more

Writing

Field notes.

Longer pieces on AI literacy, agentic prompt engineering, and the systems sitting underneath both. Written when something is worth setting down in full.

Portrait of a tired operator between two AI screens, captioned Meat Proxy, illustrating the gap between working in an AI stack and working on its architecture
LinkedIn

Working ON Your AI Architecture vs. IN It: Re-Engineering Gerber's Model.

What if we took Michael Gerber's famous E-Myth cliché: "work on your business, not in your business", and instead of applying it to a human-led company, applied it directly to an AI-centric enterprise?

Field note Read
Split diagram contrasting a Legacy Generative LLM on the left with the Jev System One on the right, separated by a decoupling gate, with Yes/No, Rate 1-5 and Select X/Y outputs
LinkedIn

System One Decision Models: Decoupling Classification from Generation

As a system builder, my workflow is rarely linear.

Field note Read
Two-tiered AI literacy: employee-level AI literacy and leadership-level strategic AI literacy, visualized as two complementary learning paths
LinkedIn

Before You Give Your Team Autonomous AI Agents, Educate Them on How to Think With Them

Many AI education programs stop at showing employees which buttons to press.

Field note Read
3 Uncomfortable Questions Before Buying AI Agents - desk with stopwatch, keys, and architectural blueprint with puzzle-piece cutouts
LinkedIn

Before Buying AI Assistants for Your Team, Ask These 3 Uncomfortable Questions

When I sit down with clients, my job isn't to push a specific system or design the tech stack right away.

Field note Read
About Me portrait with a rogue mouse cursor floating on top, flagged automatically during image processing
LinkedIn

The devil is always in the details.

I was recently updating my site and decided to upload a new "About Me" picture.

Field note Read
CerAImic Framework Configuration & Audit Panel. Three panels covering Knowledge Architecture, the Automated Refactoring Loop, and System Governance
LinkedIn

Treating Agentic Prompts Like Code: Automated Refactoring, Diffing, and Gap Analysis

My operational dashboards handle execution. But to continuously harden the system, I needed a panel that governs the knowledge logic itself.

Field note Read
CerAImic VR AI Office concept visualization showing the agent team at workstations: Neon (Executive Assistant), Genev (Data Analyst), Riley (Research Specialist), Lyra (Creative Director), Orion (Strategy Planner), Atlas (System Architect)
LinkedIn

How Do You Overengineer Outside Your Field? Lessons from Building a VR AI Office

For years, my VR headset was for escaping reality in Flight Simulator.

Field note Read
Portrait photograph of the author
LinkedIn

The Automation Trap: Why I Refused to Automate Client Billing.

They were between chatbot contracts, needed a bridge solution to keep operations moving, and wanted to know what I could do.

Field note Read
Robot holding a bouquet of balloons, standing in for an AI agent that arranged a human gift
LinkedIn

The Surprising Gift: When Your AI Agent Hires a Human

Standing at my door was a delivery woman holding a bouquet of balloons.

Field note Read
Home clothes laid out, representing agents stepping out of their work persona
LinkedIn

Beyond the Prompt: Why My AI Agents Have "Home Clothes"

I gave my agents actual "Me-Time."

Field note Read
Agent observability dashboard with per-agent metrics
LinkedIn

The Architecture of Sight: Taming Multi-Agent Chaos with Production Telemetry.

But as you transition from sandbox testing to actual business operations, a sobering reality sets in: emergence is a double-edged sword.

Field note Read
Dog eating from a bowl, illustrating the idea of eating your own dog food
LinkedIn

The Great Agentic AI Paradox: Are They Eating Their Own Dog Food?

Of course not. That lack of trust would destroy the company's credibility overnight.

Field note Read
Stylized AI worm crawling across a digital network, representing self-propagating AI-driven cyber threats
LinkedIn

The Asymmetric Digital War: The Case for Democratizing State Defense.

I'm always amazed at how fast this technology is, as an AI engineer.

Field note Read
Generated cover image contrasting rigid assembly-line control with output-quality governance for autonomous agents
LinkedIn

The Architecture of Autonomy: Why the Nerve Center Knows No Cage.

Traditionally, ITAM is designed to eliminate risk by forcing everything into rigid, uniform frameworks.

Field note Read
Celebratory photo marking a first production deployment
LinkedIn

Big milestone today: I just successfully delivered my first official AI agent consulting job! 🎉

This is just deployment number one. The infrastructure is proven, the framework is solid, and I'm ready for the next one! 🚀

Field note Read
Nested Kanban board used to govern agent output quality, with cards moving through nested columns
LinkedIn

Architectural Governance: Engineering a Gated, Multi-Layered AI Agent Pipeline.

If you don't control the structural boundaries before they code, you don't control the software.

Field note Read
Generated cover image showing a dashboard moving from desktop to mobile, representing the Nerve Center native app roadmap
LinkedIn

From Web Portal to Native Mobile: The PM Roadmap for the Nerve Center

It was an incredibly practical, hands-on event focused on native Android application development.

Field note Read
Diagram of a communication loop routing every outbound agent message through a central validation checkpoint
LinkedIn

The Communication Bottleneck.

Without visibility into what they're sending and no mechanism to correct course, you either micromanage (defeating the point) or risk brand damage.

Field note Read
Screenshot of the CerAImic Nerve Center agent interface
LinkedIn

Inside the CerAImic Nerve Center: Managing My AI Executive Assistant, Coach, and Developer.

While most of them operate under the "CerAImic" corporate family banner, there is one distinct outlier: Arnold, my personal life coach.

Field note Read
Diagram contrasting a minimal Swiss Watch design with a feature-heavy Swiss Army knife, with token cost per agent
LinkedIn

Why I'm Contributing to OpenClaw While Building My Internal Vision

While I've been absent from this feed, I have been anything but idle.

Field note Read
Idea funnel showing a concept moving from entry to a requirements round, with an application database and deployment status
LinkedIn

From Idea to Production: A Glimpse into My Autonomous Development Pipeline.

Today, I'm excited to share a milestone: my development agents have just finished their 4th complete application, from initial concept to an automated deployment on Railway.

Field note Read
Cloud dashboard showing a running deployment during a paid private pilot
LinkedIn

A note of appreciation (and a few answers).

However, to save everyone some time: The system itself is not for sale.

Field note Read
Organization chart of the agent team showing Neon at the top, then Orion and Genev, then Riley and Arnold, plus the developers and writers teams
LinkedIn

Introducing my new "Colleagues": Building a Future-Ready AI Team at Home

Meet the team I have running at home.

Field note Read
Start here

Two checks and a field guide.

The AI Discovery Journey

Twelve questions, five dimensions, one honest verdict on how ready your team actually is.

Your answers stay in your browser, and the report is on the page either way.

The EU AI Act Check

What your organisation actually does with AI, mapped onto Regulation (EU) 2024/1689.

A risk tier per use, the obligations that follow, and what is due when. Answer what you use, not a legal quiz.

The EU AI Act Guide

The law in plain language, written by the people who run the check.

Five questions an SMB actually asks, with the article references one click away.