AIaas are often stuck in a binary choice: pay the "token tax" for convenient Cloud APIs or manage the complexity of local open-source models (Llama/Mistral) yourself. Further more, the work to keep up with the model migration becomes unmanageable, as hundreds of new AI models are released already in Q1 2026. The future belongs to a hybrid architecture—but the routing logic should be as low maintenance as possible.

In this session, we introduce DIO (Distributed Intelligence Orchestration), a new open-source framework designed to bridge on-premise infrastructure and cloud capabilities. We will move beyond theory and look at the code behind the Federated Decision Engine (FDE)—the algorithm that allows you to dynamically route prompts based on privacy, cost, complexity, and more.

Session Takeaways:

The DIO Architecture: A technical deep dive into the open-source framework that decouples your application from specific model providers.

Live Integration: How to implement the DIO SDK to build a "Smart Router" that connects the best of both world for Cloud & On Prem Intelligence.

Minimize the burden of constant migrating on and off AI models as they evolve, while also optimize for key metrics like cost, quality, performance, privacy.