Rockfish is building state-of-the-art generative AI software solutions to assist enterprises in generating "synthetic data"
Many are touting the latest developments in AI as the '‘next platform shift'. At TEN13, we are excited by the evolution of AI and support the view that over time, every startup will need to adopt AI into their strategy.
We are therefore delighted to share our investment in the Pre-Seed round of US-based, Rockfish Data. Rockfish’s team of world-class researchers and PhDs has developed a state-of-the-art generative AI software solution to assist enterprises in generating "synthetic data".
It is projected that in the near future, 60% of the data used for AI and analytics projects will be synthetically generated. As such, the ability to seamlessly produce synthetic data will be critical for every enterprise looking to benefit from the advances in Artificial Intelligence; augmenting and truly leveraging their own unique data sets.
So, what is synthetic data? It is artificially generated data that imitates real-world data but is not derived from actual observations, measurements, or real-world identifiable information. Algorithms and statistical models are used to create synthetic data while maintaining the characteristics and patterns of the original data. This makes it useful for a multitude of applications, such as machine learning training and testing.
Problem and market opportunity
Within enterprises, data teams often lack access to realistic, relevant, and timely data. This can be due to restrictions on use, compliance and privacy, or even just availability of enough clean data. This affects productivity, product development, testing, and the ability to share data with third parties.
Synthetic data can be used for data augmentation (improve accuracy or expand datasets), data generation (generate data for simulations), and data privacy (remove identifying information).
However, generating high-fidelity (accurate, complete, consistent, and timely) synthetic data today is difficult. ‘Advanced algorithms’ and tools that are currently available to enterprise data teams do not provide a one-stop shop solution / platform, particularly when it comes to dealing with time series data.
Vision & Solution
Enter Rockfish.To solve this, the Rockfish solution provides enterprise data scientist teams with an end-to-end "synthetic data workbench". Their solution seamlessly integrates with existing data pipelines, arming teams with a flexible and customisable platform to frictionlessly adapt datasets and generate high fidelity, granular, privacy-compliant synthetic data.
From the moment we met Muckai Girish, Rockfish’s CEO, he exhibited remarkable clarity of vision in addressing fundamental challenges faced by enterprises. Girish, a seasoned executive in software sales and strategy, boasting over 25 years of experience with major global software and telecom companies, co-founded Rockfish alongside a world-class product and technical team.
Driving Rockfish's product is co-founder Nathan Haugo, with extensive technical expertise and experience having worked with multiple global venture-backed data and software scale-ups.
At the core of Rockfish's platform lies a proprietary architecture that has been crafted over the past decade out of Carnegie Mellon University (ranked the top program in the US for Computer Science and Artificial Intelligence), by some of the brightest minds in the field of AI - Rockfish's co-founders, Vyas Sekar and Giulia Fanti.
See below, Rockfish Co-Founders, Girish and Vyas with TEN13’s Seamus in Palo Alto
Why we invested:
Exceptional mix of technical and commercial founding team:
Girish Muckai - Founding CEO - Girish is a seasoned software sales and strategy executive with over 25 years of experience, including:
Recently Chief of Marketing and Sales at HEAL Software.
Corporate business development, strategy, and M&A at Juniper Networks, Reliance Jio, and Passage AI (acquired by ServiceNow).
A degree in Mechanical Engineering from the top university in India (IIT Madras), a PhD in operations research/manufacturing engineering from Boston University, and an MBA from Wharton.
Nathan Haugo - Co-Founder & VP Product & Engineering - leading the product development and engineering capability at Rockfish, Nathan previously held senior positions at scale ups such as Era Software (acquired by ServiceNow), Lilt (venture-backed enterprise AI company), InfluxData (venture-backed time series data company) and others.
Vyas Sekar, PhD - Co-Founder - 10 years as a Professor of computer science at Carnegie Mellon.
Giulia Fanti, PhD- Co-Founder - Giulia is an Assistant Professor of Electrical and Computer Engineering at Carnegie Mellon.
Proprietary technical architecture:
The initial wedge being targeted by the Rockfish team is in time series data, which has historically been a difficult data type for which to generate data synthetically. With over a decade of prior research and development, in combination with an intuitive, end-to-end synthetic workbench product, this team has an opportunity to provide a unique offering, and build a significant and sustainable advantage in this space.
Picks and shovels play supporting strong industry/platform shift tailwinds and massive data and AI market:
Given AI has the potential to become such a core component of the vast majority of global enterprises, synthetic data has a significant role to play in the total addressable market of big data.
We are delighted to be partnering with Girish and the team at this early stage, and excited about the journey ahead for Rockfish to become a key catalyst in enabling AI adoption at scale across enterprises.
Seamus and the TEN13 Team
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