# AI Integration for SMEs: From Idea to Production

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# AI Integration for SMEs

From initial exploration to a scalable production environment. We build pragmatic AI solutions that deliver immediate value.

## Our 4-Phase Approach

Successful AI adoption requires a structured approach. We don't just implement technology; we solve concrete business problems.

1. Discovery & Strategy
We analyze your current processes and identify where AI can make the greatest impact. No hype, just a realistic business case.

2. Proof of Concept (PoC)
We build a targeted, small-scale solution to test feasibility. In doing so, we compare various models (such as DeepSeek for specific tasks or Claude for complex reasoning) on accuracy and speed.

3. Integration & Development
After a successful PoC, we integrate the solution into your existing systems. We use proven frameworks and architectures such as [RAG (Retrieval-Augmented Generation) with vector search](https://leren.llmnet.nl/en/rag-voor-beginners) for reliable answers based on your own documentation.

4. Management & Scaling
Your application runs in production. We provide management, monitoring, and, if desired, access to powerful local AI computing power (HPC) to ensure continuity and data privacy.

## Common Use Cases by Sector

Our integrations are tailored to the specific dynamics of your industry.

### Customer Service & Support

Intelligent systems that analyze technical manuals and past tickets to assist support agents in real-time with accurate, contextualized answers (driven by vector search).

### Legal & Financial

Automated analysis of large volumes of contracts or policy conditions. AI models extract specific clauses and flag deviations, significantly shortening case processing times.*

* Please note: the time savings achieved are an estimate and depend on data quality and document structure.

### E-commerce & Retail

Dynamic generation of optimized product descriptions and personalized recommendation engines, built on a scalable web architecture.

## Frequently Asked Questions (FAQ)

Which AI models do you use?
We are model-agnostic. Depending on your use case, we deploy the most suitable technology, ranging from powerful open-source models via specific frameworks to leading commercial solutions.

Will our company data remain secure?
Yes. Security and data privacy are our starting point. We build architectures where your company data remains strictly separated from public training data, often via enterprise APIs with a zero-retention policy or via dedicated infrastructure.

How long does an average project take?
A typical Proof of Concept takes 2 to 4 weeks. A full production integration usually takes 2 to 3 months, depending on the required integrations with your existing software.

© 2026 LLMnet Consultancy. B2B AI Consultancy & Integration.