We integrate large language models into analytically well-founded, data-driven architectures – not just as showcases, but as controllable, productive solutions.
Our focus:
– LLM integration with Guardrails and controlled
– End-to-end evaluation for continuous improvement
– Analytical model selection for scalability and fit
– Combination of graph databases and SQL interfaces
– Integration of existing systems
– Multimodal interfaces (chatbots, APIs, interfaces)
We develop advanced hybrid AI pipelines – interactive, connectable and robust.
From architecture design to implementation.
If you not only want to test LLMs, but also use them productively – feel free to get in touch.
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Saganode is Live. From Idea to World to Video
Today we’re launching Saganode — a new way to build, explore, and scale stories and knowledge.
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How Banks Make AI Auditable: Our Audit Framework for Knowledge-Centric AI Systems
How banks can use AI productively without falling into the black-box trap: we present an audit and governance framework for knowledge-centric AI systems that aligns with the EU AI Act, DORA, NIS2, GDPR & more and is specifically designed for regulated environments such as banks.
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Audit Framework for Knowledge-Centric AI Systems
This document defines a pragmatic, minimum-viable audit and governance framework for organizations deploying knowledge-centric AI systems in regulated or high-trust environments. It is intentionally lightweight, but structurally rigorous. The framework is not designed to introduce additional bureaucracy, nor to prescribe a specific technology stack...
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