In a bid to address the reproducibility crisis – the challenge of data reproduction in academia – Carnegie Mellon University colleagues Vyas Sekar and Giulia Fanti brainstormed a unique idea. They envisioned the potential to leverage synthetic data in resolving this issue; an idea that resonated with Muckai Girish, an entrepreneur mindful of similar challenges plaguing his clients. Thus, Rockfish was born.
Rockfish capitalizes on synthetic data generated by AI to streamline enterprises’ operational workflows and dismantle data silos. It integrates with renowned database providers and guides users in data configuration per company policies and requirements.
Synthetic data has become a buzzword in AI, yet Rockfish predates the hype. Their intention isn’t to simply hop on the bandwagon but to differentiate their product – one proactive in ingesting data and focused on operational data. This data, associated with financial transactions, cybersecurity, supply chains etc., is essential for daily operations and is frequently fluctuating – a niche Rockfish aims to fill.
Today, Rockfish serves various enterprise clients, including the U.S. Army, Department of Defense, and the streaming analytics platform, Conviva. The company recently announced a $4 million seed funding round led by Emergent Ventures and participation from other firms, raising their total funding to approximately $6 million.
Despite an increasingly competitive market, Rockfish stays ahead by improving its approach to synthetic data, incorporating state space models among other techniques for enhanced realism and relevance. They strive for realistic synthetic data generation on a regular basis, meeting the needs of contemporary enterprises.
Original source: Read the full article on TechCrunch
