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The EU market sets your clock, not Swiss membership. Read the calendar as an architecture signal and you build one foundation; read it as a to-do list and you build a project for every deadline.

Swiss manufacturers who deliver their machine-readable information backbone for DPPs at the outset, will be well prepared for the upcoming DPP delegated acts, as well as regulatory and market challenges.

We asked a general AI and our own Data Graphs AI the same question about World Cup squad rotation. Only one could answer it with real numbers. The difference was not the model, it was the knowledge graph underneath it.

A knowledge graph turns a competition's data into something AI can reason over, not just summarize. See how Data Graphs modeled the entire FIFA World Cup 2026, then let AI predict a lineup, check its own accuracy, and generate a fully tagged match report, with hero image, written back into the graph.

Why deep graph traversal breaks most engines. How Data Graphs runs deep queries orders of magnitude faster than Neo4j, in a fraction of the memory, and with higher throughput.

In high-trust environments where information evolves constantly, measuring AI accuracy is not enough. A governed information backbone is what makes AI systems observable and defensible.

AI-powered video intelligence is no longer reserved for organizations with Netflix's engineering resources. Here is how Bitmovin and Data Graphs make it a production reality, deployable in weeks, not years.

Governed, shared reference data is the stable vocabulary your information backbone speaks in. Without it, every system upstream and downstream (yes - including AI) is guessing, and you cannot achieve machine readability.

Why the true cost of building a governed information backbone for a high-trust environment is almost always underestimated - and what that means for your build vs buy decision.

Most AI systems get answers wrong because they lack context and cannot reliably connect the dots between data points. Structuring relationships between data enables AI to reason accurately and produce reliable, production-ready answers.

Written for organizations that already have systems, already have data, and are still unable to get immediate answers to their crucial business questions.

In regulated and high-trust environments, AI reliability is a foundation problem.