AI & LLM Integration

AI Integrations

AI as a practical tool, not a gimmick

From ChatGPT integrations to custom RAG systems. I help you meaningfully deploy AI in your existing workflows and software, with attention to costs, privacy and control.

My approach

Practical

AI where it adds value, not everywhere. No hype, but results.

Transparent

Clear about what AI can and cannot do. Realistic expectations.

Privacy-aware

Data processing with attention to GDPR and business-sensitive information.

Maintainable

Solutions that still work and can be adjusted a year from now.

What I build

LLM Integrations

Integrate OpenAI, Claude, or open-source models into your application for text, analysis or conversation.

RAG Systems

AI that bases answers on your documents and data. Knowledge bases, support bots, document analysis.

Prompt Engineering

Design effective prompts for consistent, reliable AI output in production environments.

AI Workflows

Automate complex tasks by combining AI with traditional software. Classification, extraction, summarization.

Evaluation & Guardrails

Monitor and control AI output. Quality control, content filtering, fallback logic.

Fine-tuning Advice

When to fine-tune or not? Cost-benefit analysis and guidance on model adjustments.

Technologies

OpenAI API
GPT-4, Embeddings
Anthropic
Claude models
LangChain
LLM orchestration
Pinecone/Weaviate
Vector databases
Hugging Face
Open-source models
Python/FastAPI
Backend integration

Frequently asked questions

Is AI suitable for my use case?
Not every situation calls for AI. In an initial conversation I analyze whether AI actually adds value or whether a simpler solution is better.
What about the costs of AI APIs?
API costs can add up with intensive use. I help with cost estimation, caching strategies and choosing the right model for the right task.
Is my data safe?
Data privacy is a core point. I advise on local models, enterprise API plans, and data minimization to limit risks.
What if the AI makes mistakes?
AI is not perfect. That's why I build with guardrails, human-in-the-loop where needed, and clear fallback logic.

Deploy AI?

Tell me about your situation and I'll think along about the possibilities.

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