Databricks has announced several new enhancements to its Mosaic AI platform, aimed at helping enterprises deploy large language model (LLM)-powered applications. The latest capabilities focus on developing compound AI systems, evaluating them across different metrics, and governing the entire pipeline. This move creates a robust end-to-end ecosystem for building reliable gen AI apps from enterprise data. The company is strengthening its offering against Snowflake, which has been moving in the same direction.
The new features include Mosaic AI Model Training and Agent Framework, which enable the creation of retrieval augmented generation (RAG)-based compound AI systems. The platform also includes an AI Tools Catalog that lets organizations govern, share, and register tools using Databricks Unity Catalog. Additionally, the Mosaic AI Gateway provides teams with a unified interface to query, manage, and deploy open-source or proprietary models, enabling them to switch LLMs without making complicated changes to the application code.
In my opinion, these enhancements demonstrate Databricks’ commitment to providing enterprises with the tools they need to successfully deploy gen AI applications. The focus on governance and monitoring capabilities is particularly noteworthy, as it addresses concerns about the responsible use of AI.
