The problem you're facing
Adding an LLM API key to an application is easy; making it reliable, economical and compliant is not: hallucinations, exploding costs, data leaking outside Europe.
Our answer
We integrate generation with production engineering: grounding in your data (RAG), guardrails, source citation, caching and routing for costs, GDPR compliance by design.
What LaMeDuSe Technology takes care of
- Model choice per use case
- RAG architecture for grounded content
- Quality guardrails and enforced formats
- Source citation and traceability
- Cost control: caching, routing, smaller models
- GDPR compliance and European hosting
- Continuous quality evaluation
Our methodology
- 1
Context audit
Real usage, volumes, existing setup and goals: context dictates technical choices.
- 2
Tailored architecture
Argued recommendations for your context, not copied from a textbook case.
- 3
Implementation
Development and deployment by teams who use the same stack in production.
- 4
Skills transfer
Documentation, reviews and knowledge transfer for your autonomy.
Technologies
Security
Hardened configuration, secrets managed outside the code, analysed dependencies and monitoring from go-live.
Hosting
Our own platforms run on these technologies on European infrastructure: expertise is proven by usage.
Maintenance
Version watch, dependency updates and support by teams who use the stack daily.
Why LaMeDuSe Technology
We've integrated generation into our own products: the cost, quality and confidentiality trade-offs are the ones we live on our platforms.
Frequently asked questions
Based on three criteria: required quality, confidentiality and cost. A generalist model often suffices; sensitive data points to open-source self-hosting. The trade-off happens in a POC on your real cases.
Grounding in your data (RAG), source citation, constrained output formats and human validation on high-stakes content. Generative AI without guardrails is a risk generator.
They become so with the right levers: caching frequent answers, routing to smaller models, limiting context. Per-feature tracking lets you steer rather than suffer.
Yes: open-source model self-hosting on European infrastructure, or European APIs with minimisation. The choice depends on your requirements and needed quality.
Ready to turn your ideas into reality?
Contact our experts today to design and develop your custom technological solution.