Question 1

How do you actually implement AI in a business?

Accepted Answer

I find where AI creates real value, design the architecture, and build it end-to-end — running systems, not slideware.

Question 2

Can you build AI into a healthcare product?

Accepted Answer

Yes — I have architected clinical decision support, AI meal analysis and LLM health assistants on a custom model + vector database, with the privacy and reliability healthcare demands.

Question 3

Can you build a production mobile app in React Native?

Accepted Answer

Yes — I ship native iOS and Android apps from one Expo/React Native codebase, with payments, provisioning, offline-first flows and clean native integrations.

Question 4

How do you scale a Node.js backend?

Accepted Answer

With the right architecture: services split by load, event streaming, queues and caching, observability, and databases chosen per workload — proven on a platform that grew to 3M+ users.

Question 5

Can you build an MVP and then scale it?

Accepted Answer

Yes — I build MVPs end-to-end fast, then evolve the same codebase to production scale instead of throwing it away. Several of mine grew to acquisition or millions of users.

Question 6

How do you build a project with agentic AI development?

Accepted Answer

I drive AI coding agents (Claude Code, Codex, Cursor) with custom rules, hooks and context, spec-first — then gate everything with tests and AI review so speed never costs quality.

Question 7

How do you use CodeRabbit for code review and quality?

Accepted Answer

CodeRabbit reviews every pull request automatically — catching bugs, security issues and smells — as a gate alongside human review and a real test suite, so nothing weak reaches main.

Question 8

Can you build a custom AI model for my product?

Accepted Answer

Yes — self-hosted models on Ollama (Llama, Mistral, DeepSeek), fine-tuned or RAG-grounded, when you need privacy, control or a task an off-the-shelf API can’t do well.

Question 9

How do you build a RAG system?

Accepted Answer

Chunk and embed your data into a vector database, retrieve and rerank the right context per query, ground the model in it, and evaluate — so answers are accurate and cite your sources, not hallucinations.

Question 10

Which AI model should you use — Claude, GPT, Gemini, Perplexity or Grok?

Accepted Answer

It depends on the task — and the real answer is usually more than one. I pick and route across frontier models by strength, with evals and fallbacks, so you get the best result without lock-in.

Abdulrahim Klis

Ein Software-Ingenieur mit Fokus auf KI-Beratung — von der Umsetzungsberatung bis zum Bau.

Beratung — von Frontier-Tools bis zum eigenen KI-Modell

Build with the best models — Claude, GPT, Gemini, Perplexity, Grok

Ground AI in your data with RAG

Custom & self-hosted AI models

From strategy to shipped product

Map the value

Design the architecture

Build it

Hand it over

Häufige Fragen

Can you build AI into a healthcare product?

How do you actually implement AI in a business?

Can you build an MVP and then scale it?

How do you build a RAG system?

Projekte

OptAI

Leadtech — aichatapp.ai

IMAGO Images

Sumus

Mana

VW Group

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