First startup acquired by a multinational after just 5 years? Recurve founder Tony Dongni Ren reveals the game of entrepreneurship and exit

First startup acquired by a multinational after just 5 years? Recurve founder Tony Dongni Ren reveals the game of entrepreneurship and exit

This episode, we're joined by Tony Dongni Ren, founder of Recurve and founding CEO of Yimian Data.

Tony Dongni Ren is a serial entrepreneur who returned to data science after a successful exit. After earning his bachelor's, master's, and PhD in computer science from the Hong Kong University of Science and Technology, Tony worked at Tencent, the National Institute of Informatics in Tokyo, and Huawei's Noah's Ark Lab in Hong Kong, developing mobile big data analytics and processing platforms. He then joined Kuaibo Technology, where he led R&D in machine learning and computer vision. Just six months later, Kuaibo became the first domestic video app to launch poster/film screenshot recognition and facial recognition systems, with over 500,000 daily API calls.

In early 2014, Tony left Kuaibo and co-founded "Yimian Data" with his then-partners, focusing on data mining and analytics services for investment and consumer brands. In 2016, ZhenFund became their angel investor. Following a period of rapid growth, Yimian Data was fully acquired in 2019 by Ascential, a multinational group specializing in data services, becoming an important branch and strategic foothold for the company in China.

After a coveted equity windfall and successful "exit," Tony decided to start fresh. In 2023, he reunited with his original team to found "Recurve." This time, they're focused on building Data & AI infrastructure, committed to redefining how data flows and is used within enterprises through generative AI technology — eliminating barriers between people and data.

In this episode, Tony draws on his dual identity as both a veteran who has experienced the full startup cycle and a founder back at the starting line, sharing valuable lessons and industry insights from his two entrepreneurial journeys. Compared to his first startup, what prompted him to embark on this new one? What is the new company's product? How does he view Yimian Data's successful acquisition? What challenges did the acquisition process present? As a technical founder without a business background, how should one negotiate valuation with investors? Looking back from where he stands now, which decisions might he have made differently?

We hope this conversation also offers some "begin with the end in mind" inspiration for technical founders currently facing similar crossroads.

[Guest] Tony Dongni Ren — Founder and CEO of Recurve, Founder of Yimian Data

[Timeline] 02:15 — The origin of the name "Recurve"

05:56 — What sparked the second entrepreneurial journey

10:16 — How does data function within enterprises?

14:24 — When everyone wants to mine for gold, start selling shovels

19:16 — A "lucky" acquisition born of serendipity

20:43 — The mindset shift between continuing to build and accepting acquisition

24:44 — Due diligence as a two-way street

31:10 — What qualities mattered most in an acquirer?

34:39 — Anchor your exit strategy from day one

39:48 — What difficulties arose during acquisition?

49:42 — If doing it over, what would you most want to change?

53:36 — Valuation and negotiation tactics: a post-mortem

59:21 — What does being acquired actually feel like?

1:06:05 — Entrepreneurship = validating opportunities spotted while working for others

1:09:33 — Once you're the boss, remember not to "help" in ways that hinder

[Additional Resources]

MDS (Modern Data Stack): A collection of cloud-based tools and technologies that help organizations collect, store, process, and analyze data. It is designed to simplify data management, improve data accessibility, and drive better decision-making across the organization.

Data & AI Infra (Data & AI infrastructure): Refers to the middleware layer connecting computing power and applications, providing foundational AI stack technologies that support upper-layer AI algorithm applications and enable accelerated AI computing and deployment. Data & AI Infra covers data preparation, model training, model deployment, and application integration — analogous to the basic software layer of computer systems and the PaaS tier in cloud computing's three-layer architecture.

Further Reading:

www.qlik.com

The Modern Data Stack: Past, Present, and Future | dbt Labs

Emerging Architectures for Modern Data Infrastructure: 2020 | Andreessen Horowitz

"The Hidden Hundred-Billion Market Under AI Infra" – woshipm.com