Building LLM Applications
RAG architectures, agents and MCP, output evaluation, security and on-premise LLM deployment.
Learn more →We turn your AI idea into a product that people actually use and that creates business value. From product design and model development to the interface and production, one team manages the entire process.
We clarify product goals, users and data.
We rapidly build a first version with the most critical features.
We complete security, scalability and integrations.
We improve the product based on user feedback and metrics.
RAG architectures, agents and MCP, output evaluation, security and on-premise LLM deployment.
Learn more →Classification, regression, model evaluation and feature engineering on real-world datasets.
Learn more →A hands-on workshop built around your own use cases. You leave with a prioritised, actionable AI roadmap.
Learn more →It depends on scope, data readiness and integration needs. Usually a first version (MVP) with core features is built first and grown with user feedback.
This is defined in the project contract; deliverables include source code and technical documentation.
Yes. Knowledge transfer is part of the deliverables, so your team can maintain the product.
Either. We decide together based on data sensitivity and regulatory requirements.
Tell us about your training, consulting or software needs and we will get back to you within 2 business days.