Rockfish Aims to Transform Enterprise Data Management with Synthetic Solutions

Rockfish, a startup specializing in generative AI, is tackling the growing demand for synthetic data by providing solutions that help enterprises streamline their operational workflows. The journey began in early 2022 when Vyas Sekar discussed the idea with his long-time friend Muckai Girish, leading to a venture that has quickly gained traction in the tech and enterprise sectors.

Rockfish Aims to Transform Enterprise Data Management with Synthetic Solutions
Rockfish Aims to Transform Enterprise Data Management with Synthetic Solutions

Rockfish, a startup specializing in generative AI, is tackling the growing demand for synthetic data by providing solutions that help enterprises streamline their operational workflows. The journey began in early 2022 when Vyas Sekar discussed the idea with his long-time friend Muckai Girish, leading to a venture that has quickly gained traction in the tech and enterprise sectors.

Sekar, along with his colleague Giulia Fanti from Carnegie Mellon University, had been addressing the "reproducibility crisis" in academia, focusing on creating synthetic data to resolve challenges in replicating studies. While academia was grappling with this issue, Girish recognized that similar problems existed within enterprises, where fragmented and siloed data hindered effective operations. After engaging with businesses and validating the problem, the duo decided to launch Rockfish in June 2022.

Rockfish offers a platform that integrates with major database providers such as AWS and Azure, enabling organizations to generate synthetic data tailored to their needs. Girish emphasized that the company’s goal was to create a solution that businesses could rely on daily. The platform specifically targets operational data, which includes areas like financial transactions, cybersecurity, and supply chain logistics. These domains constantly generate large volumes of data, making them ideal for Rockfish’s continuous ingestion and processing capabilities.

The startup has already secured enterprise clients, including Conviva, a streaming analytics platform, and government entities such as the U.S. Army and the U.S. Department of Defense. These partnerships highlight the relevance of Rockfish’s technology in both corporate and public sectors. According to Girish, focusing on operational data allows the company to differentiate itself from competitors in the synthetic data market.

To fuel its growth, Rockfish recently raised $4 million in a seed round led by Emergent Ventures, with additional backing from Foster Ventures, TEN13, and Dallas VC, bringing its total funding to $6 million. Anupam Rastogi, managing partner at Emergent Ventures, cited the team’s technical expertise and enterprise-oriented approach as key factors behind the investment. "This is a space that we think is very technically sophisticated, and having that technical strength around the table is really critical," Rastogi explained.

As synthetic data continues to attract attention across industries, Rockfish faces competition from established players such as Tonic AI, Mostly AI, and Hazy. These companies have collectively raised significant venture capital, underscoring the potential of the market. However, Girish believes Rockfish’s focus on operational data and its ability to continuously process real-world data sets give it an edge. “If you put all of this together for enterprises, it actually is very relevant and realistic. So that’s the key to this,” he said.

Looking ahead, Rockfish plans to expand its capabilities by integrating additional models, such as state space models, and enhancing the platform’s end-to-end features. The company is committed to building synthetic data solutions that are not only technically robust but also seamlessly integrated into enterprise workflows.

As the demand for innovative data solutions grows, Rockfish positions itself as a significant player in addressing the complex needs of modern businesses through its synthetic data technology.