Custom AI Software That Works With Your Own Data

For most businesses, the question is no longer whether to use AI, but how to use it safely with their own data. A general chat tool does not know your contracts, product catalogue or internal procedures; it cannot create a record in your ERP, and it cannot tell which employee is allowed to see which information. AI software development closes that gap: the model becomes one component of software connected to your data, your systems and your rules. We build this software end to end for companies across Europe, working remotely and communicating in English, German or Polish. If a quick chatbot or a workflow built on existing tools is all you need, our AI automation service is usually the faster starting point; this page covers projects that call for custom software.

We do not tie a project to a single model. For each use case we compare the OpenAI, Anthropic Claude and Google Gemini APIs with open-weight models such as Llama, Mistral or Qwen, weighing answer quality, cost, latency, context window and where the data is processed. The architecture keeps the model replaceable, so a better or cheaper model later does not mean rewriting the software. Connections to your ERP, CRM or document archive follow the same discipline as our API and system integration work. For answers grounded in company knowledge we use retrieval-augmented generation (RAG): documents are split and indexed in a vector database, each answer is based on the relevant passages, and users only receive answers from documents they are authorised to see.

The quality of AI software shows in measurement, not in a demo. At the start of the project we build an evaluation set from your real questions and expected answers, and every change to a prompt, model or data source is tested against it. In production, answers, costs and errors are monitored, whether the AI runs as an internal tool or inside your own SaaS product. Critical steps such as a reply going to a customer, a change to a record or an approval keep a human in the loop, and when the model is uncertain it hands the task to a member of staff.

Data protection is the first architectural decision, not an afterthought. We document which data goes to the model, which is masked and where everything is stored. A data processing agreement under the GDPR, hosting in the EU or on your own servers, access logging and safeguards against LLM-specific risks such as prompt injection are part of the scope. We also take the EU AI Act into account in the design, for example by making it clear to users when they are interacting with an AI system.

Everything starts with a free first call. We clarify the use case, data sources and integrations and turn them into a written scope; for clearly scoped work you receive a written quote within 24 hours. Where it helps, a small proof of concept on your real data comes first. The delivery date is set in the contract after scope approval, and you receive weekly progress reports. On handover you get the source code, prompts, evaluation set and all accounts; after launch we look after maintenance and model updates together with you.