The HMS Blog

Erfahre, wie Atomic Delivery Teams Unternehmen helfen, Generative AI Projekte erfolgreich von der Idee in die skalierbare Produktion zu bringen. Der Artikel zeigt die wichtigsten Rollen, Fähigkeiten und Prinzipien für nachhaltige AI Wertschöpfung.

How Multi-Agent Language Models Make the Creation of Complex Documents More Accurate, Faster, and More Structured.

Souveräne IT-Architekturen sichern Kontrolle über Daten und Systeme, ohne Flexibilität einzuschränken. Anhand praxisnaher Beispiele zeigen wir, wie Organisationen Abhängigkeiten reduzieren und durch bewusste Technologieentscheidungen langfristige Resilienz erreichen.

Vector stores are at the heart of modern GenAI applications. However, scaling them efficiently is more complex than it seems. From metadata management to hybrid search to ingestion pipelines: Here, you’ll learn about common pitfalls and how to avoid them based on real-world project experience.

Early tracing and testing of LLM calls identify issues before they become costly, thereby accelerating the development, quality, and time-to-market of GenAI solutions.

In this article, you’ll learn how the Model Context Protocol (MCP) structures the interaction between the host, client, and server, what security considerations are relevant, and what typical application workflows look like. This article is intended for architects, developers, and IT decision-makers who want to integrate LLMs securely and scalably into business processes.

How can large language models effectively process large volumes of documents? In our new blog post, we highlight the key challenges—limited context windows, throughput issues, and the balance between speed and completeness—and present proven strategies from real-world projects.

Global companies manage vast amounts of complex knowledge—from regulatory filings to sales documents. Traditional search quickly reaches its limits in this context. Retrieval-Augmented Generation (RAG) chatbots promise a solution, but scaling them requires careful planning. In this article, we highlight the five biggest challenges and the proven best practices that companies can use to implement sustainable, compliant deployments worldwide.

LLMs offer enormous potential, but hardware often becomes the real bottleneck. Learn what really matters when it comes to balancing performance, stability, and costs as you scale your AI infrastructure.