Insights
Perspectives on intelligent digital transformation
This is where SilverQ shares what holds up in practice, where the typical risks lie, and how companies can make sound decisions about strategy, systems, and data.
Not every AI trend matters. Not every automation effort makes sense. And not every integration is built to last. Many companies are under growing pressure today: to become more innovative, accelerate processes, make better use of knowledge, and build smarter products. But between interest and impact lies one decisive question: what actually makes sense for your own business?
This is exactly where our insights begin. We focus on the topics that truly matter in practice. Where does measurable value emerge? Which risks are often underestimated? What conditions need to be in place so that AI does not just impress, but works reliably, securely, and sustainably?
Our perspective is deliberately practical. We do not think in buzzwords, but in systems, workflows, responsibilities, and business value. Because good decisions do not come from hype. They come from clarity.
Articles
Connecting Remote MCP securely: a demo project
This article explains why a remote MCP server in an enterprise setting is not just an interface topic. It requires a clean identity, token, and authorization architecture, and an open-source demo shows in a concrete, transparent way what that can look like.
Security architectures for AI agents
This article shows why MCP on its own is not a security architecture, and why productive agent systems quickly become a risk without short-lived tokens, clear authorization, and gatekeepers in front of them.
The end of software architecture?
This article explains why AI agents do not make good software architecture obsolete. They make it even more important. At its core is the question of how architecture and context management need to work together so AI can support development precisely, efficiently, and sustainably.
How AI can support SBOM work under the Cyber Resilience Act
This article outlines how AI can help companies create Software Bills of Materials more efficiently, understand regulatory requirements more clearly, and reduce the implementation effort surrounding the Cyber Resilience Act.
Using AI in business with legal certainty: orientation instead of hype
This article shows how companies can use AI without losing sight of responsibility, governance, and legal certainty. It clearly separates technical feasibility from business liability and explains why a controlled entry point is more sensible than either blanket bans or rushed action.
Resources
Open-source project: mcp-oauth-demo
This project shows how to build a protected MCP server with Keycloak for user authentication and server-side GitLab access in a way that keeps both user passwords and API tokens away from the client.