Technologies
OpenAI / Anthropic APIs
Production integrations with the OpenAI and Anthropic (Claude) APIs: the right model for the job, retrieval over your own data, agents with guardrails, and costs you can predict. AI engineering, Bydgoszcz.
The model APIs from OpenAI and Anthropic are the engine behind every AI feature I build. The engineering is in everything around them: choosing a model per task, grounding answers in your data, structuring outputs so other systems can use them, evaluating quality and keeping the bill under control. Based near Bydgoszcz, I integrate these APIs into stores, content platforms and internal tools for companies across Poland.
What the integration covers
- Model selection: GPT and Claude models matched to the task by quality, latency and price, with fallbacks between providers.
- Retrieval (RAG): embeddings and vector search over your catalogue, documents and knowledge base, so answers cite your data rather than guess.
- Structured output and tool use: JSON schemas, function calling and agent loops that read and write to your systems safely.
- Evaluation and observability: test sets, automatic scoring, logging and tracing, so quality is measured, not assumed.
- Cost and safety: caching, batching, rate limits, prompt injection defences and data-handling that respects GDPR.
If you have a use case and want it to work reliably in production rather than in a demo, this is the layer that makes the difference. Bring the problem, I'll bring the models and the engineering.