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Project One.

The Concept

Delivering an AI-Native ODA canvas.

Scope & key activities

The scope of the project is to deliver a live demonstration of a running AN Agent on the AI-Native ODA Canvas, showing the end-to-end path from data ingestion and reasoning through operator execution to service recovery. This will serve as the reference implementation for CSPs accelerating AI-native adoption.

The project Members will showcase a live demo at DTW Ignite in June 2026 in Copenhagen; with a Beta version showcased at MWC in February 2026 in Barcelona.


Objectives & outcomes

The objectives are to enable a unique “one-to-many” innovation model and to demonstrate a working reference implementation of the AI-Native Blueprint v1.0 principles.

The expected outcomes include:

  • A Kubernetes-based Canvas running on AWS.
  • Installed Databricks (with curated dataset) and integrated CKAN catalogue.
  • Installed MuleSoft/AWS MCP for A2A interaction.
  • Installed AWS Bedrock for model hosting.
  • Exposed Canvas operators (Data, Interaction, Model) as microservices.
  • Validated operator flow through unit testing with stubs/logs.
  • Running Autonomous Network Agent (fault management).


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Participants

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