Building and Customizing GenAI with Databricks: LLMs and Beyond

neub9
By neub9
2 Min Read

Businesses have widely embraced Generative AI, with many organizations planning to build their own custom LLMs or other GenAI models. However, some may lack the necessary tools for developing models trained on their own data. The shift to Generative AI requires a reshaping of data management, with Data Lakehouses becoming the new modern data stack. These advanced data architectures are essential in harnessing the full potential of GenAI, enabling faster, more cost-effective, and wider democratization of data and AI technologies.

The Databricks Data Intelligence Platform is an end-to-end solution that supports the entire AI lifecycle, providing organizations with more control, engineering efficiency, and lower total cost of ownership. It stands out as the sole provider capable of offering comprehensive services tailored to develop proprietary models.

This blog explores why companies are using Databricks to build their own GenAI applications and explains how organizations can utilize the platform to fine-tune, govern, operationalize, and manage all data, models, and APIs on a unified platform while maintaining compliance and transparency. Additionally, it provides insights into leveraging the Databricks Data Intelligence Platform as a company progresses along the AI maturity curve, fully leveraging proprietary data.

The Databricks Data Intelligence Platform offers complete control, production-ready capabilities, and cost-effectiveness, enabling organizations to maintain industry leadership with differentiated applications built using GenAI tools. Organizations can take advantage of intelligent data insights, domain-specific customization, and simple governance, observability, and monitoring. The platform supports organizations at each stage of the AI maturity curve, from data preparation to prompt engineering and retrieval augmented generation.

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