Contact

Advice on AI from someone who writes the code.

Who this is for

Executives and business owners in Saudi Arabia who know AI matters and want a straight answer on what to do about it.

What I do

I advise on AI strategy, I build the systems myself, and I train teams to use them properly. In Arabic and English.

How I can help

Four ways to engage, below. The fastest is a short call about your actual problem.

Kareem Mukhtar
0Systems delivered
0Workflows automated
AR·ENBilingual delivery
1Builder, no team
01 · How to engage me

Four ways to work with me.

You get one person who has done the strategy work and also builds the systems. Nothing gets lost between the plan and the product. Scope and price stated up front, in writing.

E·01

Advisory

Strategy from the person who will build it.

For leadership teams deciding what to do about AI

  • Opportunity mapping tied to your P&L
  • Honest build, buy, or wait decisions
  • Architecture & vendor review from someone who builds
  • Executive working sessions, not lectures
Model · Monthly retainer
E·02

Rapid Build

A working system in weeks.

For teams that need the thing to exist

  • Scoped to output, delivered to production
  • Full stack: FastAPI · React · AWS · Claude
  • Multi-tenant, bilingual where it matters
  • Handover, or straight into Managed Ops
Model · Fixed price per output, not billed hours
E·03

Managed Ops

I keep running what I build.

For systems that should keep getting better

  • Hosting, monitoring, iteration
  • Upgrades as better models come out
  • New features scoped as outputs
  • One accountable person, no ticket queue
Model · Monthly, scoped per system
E·04

AI Education

Hands-on, practical training.

For teams where adoption is the bottleneck

  • Executive sessions: what AI changes for your P&L
  • Operator workshops, per function
  • Build-along training on your real workflows
  • Arabic & English delivery
Model · Per cohort or per day
02 · What I build

Four kinds of systems, all running today.

Each product line links to a live system in the proof section below.

P·01

Knowledge AI

Ask questions, get answers from your own documents and data.

Assistants and analysts grounded in your own material: policies, reports, portfolios, statistics. Answers with sources, in Arabic and English.

Done properly: answers grounded in your documents with citations, access controls respected, and it says "I don't know" instead of guessing.

Running today as
P·02

Decision Intelligence

Dashboards you can question.

Executive dashboards where the chart answers follow-up questions. Narrative briefs, what-changed views, decisions traced back to the data.

Running today as
P·03

Operations & PM Systems

The systems that keep delivery organized.

Portfolio, PMO and back-office platforms. Multi-tenant, synced live to the tools you already run.

Running today as
P·04

Custom Workflows

The whole deliverable, start to finish.

Pipelines that produce the finished artifact: the deck, the report, the analysis. Generated, checked, fixed, delivered.

Running today as
03 · The proof

Built by one person. All in production.

Everything below is live or delivered. I built each system end to end, alongside a full-time job and a family. Five run on FastAPI · PostgreSQL · React · AWS · Claude; one on Microsoft Power Platform. Client names withheld where contracts require; sectors and scale are accurate.

04 · Before you build

Read this before you buy any AI system. From anyone.

Five things I tell every organization that asks. They hold whether you build with me or with someone else. If a proposal you received fails these checks, I'm happy to give a second opinion.

G·01

Know where your data lives

Data residency matters, especially for government and regulated sectors. There are in-Kingdom and on-premise options, including open models running on your own servers when data cannot leave your network. Ask this question first, not after the contract.

G·02

Open or hosted models: it depends

Sometimes a smaller open model inside your network is the right answer. Sometimes a frontier model behind an API is. Anyone who always gives you the same answer is selling, not advising.

G·03

Build with proper technical people

AI systems fail differently from normal software: confidently wrong answers, silent breakdowns, flows that go wrong at step seven of ten. You need security review, testing, monitoring, and human checkpoints designed in from the start. A demo is not a system.

G·04

Ask for the failure plan

Before anything goes live, you should know what happens when the model is wrong, how you will find out, and who is accountable when it is. If your vendor has no answer, that is your answer.

G·05

Start narrow

One workflow done properly beats a platform vision on a slide. Prove value on something small and real, then expand from what worked.

05 · The person

Consulting taught me the decisions. Building keeps me honest.

K.M.Kareem Mukhtar

I have worked in management consulting and product management for years, including at EY and Delta Partners, and I have been building software the whole time. The two sides feed each other. Consulting taught me how organizations actually make decisions. Building keeps me honest about what the technology can really do. I am based in Riyadh and work in Arabic and English.

B·1Building something real teaches you more than planning something perfect.
B·2Most organizations do not need more meetings about AI. They need one working system.
B·3Tools should make people more capable, not replace their judgment.
B·4If I am not the right person for a job, I will say so.
06 · Get in touch

Tell me what you're trying to do.

The fastest way to start is a short call about your actual problem. If I can help, I will tell you how and what it costs. If I cannot, I will say that too.

I usually reply within 48 hours, Riyadh time.