Databricks Partners with OpenAI to Embed GPT-5 and Other Models into Its Platform

Databricks will bake OpenAI models into its products in $100M bet to spur enterprise adoption
TechCrunch

Key Points

  • Databricks signs a multi‑year deal with OpenAI worth at least $100 million.
  • OpenAI’s models, including GPT‑5, become native to Databricks’ platform and Agent Bricks.
  • Customers can access the models via SQL or API, enabling secure AI applications on enterprise data.
  • The agreement mirrors a prior $100 million revenue‑target deal Databricks made with Anthropic.
  • Early demand includes interest from Mastercard and other enterprise users.

Databricks announced a multi‑year partnership with OpenAI that integrates the AI firm’s models—including GPT‑5—into its data platform and AI product, Agent Bricks. The deal, valued at a minimum of $100 million, gives Databricks customers secure, native access to OpenAI’s models via SQL or API, allowing them to build AI‑driven applications on top of enterprise data. The partnership builds on earlier work that added OpenAI’s open‑weight models, gpt‑oss 20B and gpt‑oss 120B, to the platform, and follows a similar revenue‑target arrangement Databricks struck with Anthropic. Early customer demand, including from Mastercard, signals strong interest in the combined offering.

Deal Overview

Databricks disclosed a multi‑year agreement with OpenAI that commits the data company to pay a minimum of $100 million over the life of the deal. The arrangement does not specify a duration, but it mirrors a previous revenue‑target deal Databricks reached with Anthropic, which set a $100 million target over five years. Under the terms, Databricks will pay the full amount regardless of the revenue generated by the OpenAI models, providing OpenAI with predictable income while Databricks assumes downside risk.

Product Integration

The partnership places OpenAI’s suite of models, highlighted by the latest GPT‑5, directly into Databricks’ data platform and its AI development environment, Agent Bricks. Customers can invoke the models through SQL queries or via API calls, enabling them to build and deploy AI agents that operate on secure, corporate data. Agent Bricks also offers tools to benchmark model performance on specific tasks and to fine‑tune results for tailored outcomes. The integration expands on Databricks’ earlier inclusion of OpenAI’s open‑weight models, gpt‑oss 20B and gpt‑oss 120B, added to the platform roughly two months prior.

Financial Terms

The $100 million minimum payment represents the baseline revenue that Databricks must deliver to OpenAI, irrespective of actual model usage revenue. If usage generates more than the baseline, OpenAI stands to receive additional earnings; if it falls short, Databricks will still be obligated to pay the full amount. This structure provides OpenAI with a steady income stream as it scales its data‑center infrastructure, while Databricks accepts the financial risk in exchange for a competitive edge in enterprise AI.

Customer Impact

Early responses from enterprise customers indicate strong demand for native, secure access to OpenAI’s models within the Databricks environment. The partnership has already attracted interest from high‑profile organizations such as Mastercard, which seeks to leverage the combined capabilities to develop AI‑driven applications that tap into their corporate data securely. By embedding advanced generative AI directly where data resides, Databricks aims to simplify experimentation, deployment, and scaling of AI agents for its clients.

Industry Context

The collaboration underscores the accelerating race to embed generative AI into the enterprise stack. Companies across sectors are looking for solutions that allow them to harness powerful language models while maintaining data security and compliance. Databricks’ move to incorporate OpenAI’s flagship model aligns with broader market trends where cloud‑native data platforms are becoming central hubs for AI workloads. The deal also reflects a growing pattern of AI firms securing multi‑year revenue commitments from major platform providers as the industry matures.

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