Nokia and Databricks announced the completion of a joint proof of concept demonstrating a unified, cloud-agnostic data platform intended to support AI-driven autonomous networks, according to a statement from the companies.

The proof of concept focused on a real-time performance management use case, simulating analytics ingestion at a scale comparable to that of a tier-1 telecom operator. Engineering teams from both companies developed a joint architecture designed to handle large-scale, real-time data ingestion to feed network data to AI agents for automated, cross-domain decision-making.

The project addressed the challenge of fragmented data environments in telecom networks, which typically rely on hundreds of siloed operational and business support systems with separate data architectures. The PoC validated the ability to create data pipelines once and deploy them across different platforms without modification, running on both Databricks and an open-source stack based on Apache Flink, Kafka, and Iceberg.

Additional technical outcomes included vendor-neutral data logic design using Python, an automated compiler that translates abstract workflows into platform-native formats, and an AI agent capable of generating new data products from natural language prompts.

"Teaming up with Databricks represents a big step as we work toward building the types of data foundations required for next-generation autonomous networks," said Oguz Sunay, CTO AI and Autonomous Networks, Nokia.

"Our collaboration with Nokia demonstrates how a unified data platform can help simplify operations and unlock the value of AI across network domains," said Nevash Pillay, Global Head of Telecommunications Industry, Databricks.

Nokia and Databricks said they plan to continue their collaboration to enhance autonomous network capabilities for telecom operators.