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Rubrik Acquires Predibase to Fuel Generative AI Growth

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### Predibase Acquisition Adds AI Talent, Cost-Optimization, and Fine-Tuning Model Tech

**By Michael Novinson**
*[Read more about Michael on Twitter](https://www.twitter.com/MichaelNovinson)*
*June 25, 2025*

![Predibase Acquisition](https://130e178e8f8ba617604b-8aedd782b7d22cfe0d1146da69a52436.ssl.cf1.rackcdn.com/rubrik-to-purchase-predibase-to-power-generative-ai-growth-showcase_image-7-a-28816.jpg)
*Predibase co-founder and CEO Devvret Rishi and Rubrik Chief Business Officer Mike Tornincasa (Images: Rubrik)*

Rubrik’s strategic move to acquire startup Predibase seeks to address significant roadblocks in the deployment of agentic AI technologies within enterprises. This acquisition is not merely a business transaction but a concerted effort to facilitate the transition from AI proof-of-concept projects to scalable, production-ready applications without sacrificing trust or efficiency.

### The Potential of Agentic AI

According to Mike Tornincasa, Rubrik’s Chief Business Officer, their commitment to generative agentic AI stems from its ability to enhance productivity across organizations. However, he highlights that adoption is often stymied by three main factors: the need for governed and trusted data, the accuracy and optimization of deployments, and a significant talent gap in the AI field. While Rubrik excels in providing trustworthy data, the integration of Predibase is expected to address the latter two challenges.

Predibase, founded in 2021 and led by Devvret Rishi since October 2023, has raised $28.5 million, demonstrating strong investor confidence. Its mission aligns perfectly with Rubrik’s vision to democratize AI access, ensuring that enterprises can harness AI-powered advancements effectively.

### Overcoming Barriers to AI Deployment

Rubrik recognizes that while its Security Cloud offers a robust foundation for trusted data, enhancing model performance and managing costs requires additional capabilities that Predibase can offer. They aim to optimize the deployment of AI applications, recognizing that many organizations find it challenging to progress from pilot projects—often limited to internal use cases—to more expansive, external-facing applications.

Rishi articulates this gap, stating that for organizations to feel comfortable scaling generative AI applications, they must bridge hurdles related to data management, governance compliance, and model accuracy.

### The Role of Rubrik’s Data Lake

One of the innovative aspects of this acquisition is the integration of Rubrik’s data lake, which centralizes enterprise data while ensuring compliance. Tornincasa explains how this ensures AI models can access high-quality data securely. The addition of Predibase’s model-hosting and tuning platform means organizations can customize their AI models within a secure environment.

Rubrik envisions offering a comprehensive, end-to-end solution that will resonate across the market, not just with their existing customer base.

### Enhancing Accuracy and Trust

The struggle for enterprises often lies in surpassing the accuracy threshold of 70-80% in generative AI applications. Rishi mentions that achieving a benchmark accuracy of over 90% is essential for large-scale, production-grade deployment, which is where Predibase’s post-training capabilities provide a strategic advantage.

By allowing enterprises to use their data to fine-tune models, Predibase intends to enhance accuracy significantly, facilitating more trustworthy and reliable implementations of AI.

### Security and Governance Integrated into AI

Data security and governance are paramount for organizations looking to expand AI applications. Rubrik’s robust identity-based access management ensures that data usage is well-regulated, preventing misuse—whether accidental or intentional. Tornincasa stresses that this approach is fundamental for enterprises aiming to build secure generative AI applications.

Rubrik’s established expertise in data security equips them to support organizations attempting to navigate the complexities of AI adoption.

### Broadening AI Accessibility

While leading tech companies may have the expertise to deploy advanced AI models, many enterprises do not. This is where the integration of Predibase becomes crucial; it offers less technically sophisticated organizations the ability to harness AI effectively. The aim is to streamline the complexity often associated with AI deployments, providing a user-friendly interface and reducing operational overhead.

Tornincasa emphasizes that while Predibase has succeeded with innovative companies that have machine-learning expertise, it intends to create pathways for the broader market lacking such capabilities.

This acquisition signifies a transformative step toward overcoming barriers to AI adoption, enabling a wider range of enterprises to tap into the generative and agentic AI revolution. By marrying Predibase’s technological innovations with Rubrik’s robust security infrastructure, the collaboration sets the stage for a new age of AI deployment.

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