Meridian Ventures was born out of a shared experience: deferred MBAs.
AI video generation startup Runway doesn’t have the typical Silicon Valley pedigree. No Stanford founders, no ex-Google founders, no nine-figure seed round that bought them time to ignore revenue. Its three founders — two from Chile, one from Greece —
met at NYU’s Tisch School of the Arts and built the company in New York.
Runway also could be, depending on who you ask, one of the most consequential AI companies today. Not because of what it has built, but because of what it is trying to build next.
For the past several years, the AI industry has largely operated on the premise that intelligence lives in language. Large language models like OpenAI’s ChatGPT and Anthropic’s Claude reflect that bet.
Runway, alongside other competitors, is making a different one. Its founders believe the next form of AI intelligence won’t be built from text, but from video and world models that learn how the world works, not just how humans describe it. That distinction sounds academic. Its implications are not.
Runway co-Founder and co-CEO Anastasis Germanidis said training models directly on observational data from the world is the next frontier of AI. The companies that get there first, he argues, won’t be the ones who perfected language.
“We’re basically bound by our own understanding of reality,” Germanidis told TechCrunch from Runway’s homey sunlight-filled headquarters near Union Square.
“Language models are trained on the entire internet, on message boards and social media, on textbooks — distilling the existing human knowledge,” Germanidis continued. “But to get beyond that, we need to leverage less biased data.”
Founded in 2018, Runway built its reputation on video-generation models — including its latest Gen-4.5 — and AI tools that let people turn text prompts into editable, cinematic content.
Today, Runway’s technology powers production workflows for filmmakers and ad agencies, and the company has signed deals with major media players like Lionsgate and AMC Networks. Its tools have even been used in films such as “Everything Everywhere All At Once.”
Runway is now valued at $5.3 billion and, according to one of its founders, added $40 million in annual recurring revenue in the second quarter of 2026.
If Runway’s bet that video generation is the path to world models pays off, the result will be felt from Hollywood to drug discovery. If it doesn’t, Runway risks being outpaced by competitors with far deeper pockets — Google chief among them.
Taking the leap
Within the last six months, the startup has put its plan into action and expanded beyond video generation, launching its first world model in December, with plans to launch another this year. (World models are AI systems that simulate environments well enough to predict how they’ll behave.)
Runway isn’t alone in its pursuit of turning physics-aware video models to world models, with near-term use cases in interactive entertainment, gaming, and robotics training. Startups Luma and World Labs are on a similar trajectory, and Google has pointed its Genie world model in the same direction.
Everyone is after some version of the same thing: AI that solves humanity’s hardest problems. That’s far from Runway’s original product, but it’s the result of both emergent capabilities in the technology and founders who were predisposed to follow where it led.
For his part, Germanidis sees world models as scientific infrastructure. The more sensory data and observations you train a single model on, the closer you get to a working digital twin of the universe — one you can run experiments on faster than any lab could. Much of the scientific process is just waiting on results, he points out. If you could compress that waiting, you could compress progress itself.
“If we can build a better scientist than human scientists, we can accelerate progress in how we understand the universe and how we solve problems,” Germanidis said.
The moonshot
Runway streetwear merch at the company's AI Summi
Meridian Ventures was born out of a shared experience: deferred MBAs. Now, founders Devon Gethers and Karlton Haney have raised a $35 million fund to back pre-seed and seed-stage companies started by people like them.
Gethers, 29, told TechCrunch the idea for a firm arose after he met Haney in Harvard’s MBA deferred admission program in 2020.
Gethers grew up in poverty in Washington State, studied behavioral science and finance at the University of Utah, then moved into private equity before launching a company of his own (which he later exited). Haney, meanwhile, grew up on a farm in Arkansas, raising chickens, birds, and “anything that flew,” Gethers said about his business partner.
Haney, 28, went on to study industrial engineering at the University of Arkansas and worked as an investor at the family office, The Stephens Group. The two came together in 2023 with the idea of launching a firm that backed people who had also deferred MBAs.
“Our thesis is going against a bit of the grain, the rhetoric you hear in Silicon Valley that MBAs don’t make good founders,” Gethers said, referring to the belief that an MBA prepares students for corporate culture, not the flexible, free-wheeling world of Silicon Valley.
To prove their thesis, Gethers and Haney went out and cold-called prospective limited partners and knocked on doors until they raised $2.5 million as a proof-of-concept fund to back 45 companies.
The two headed off to Harvard Business School in summer 2023 and about a year into it, decided to try and raise their first institutional fund. The funding environment was tough, but the pair ended up raising an oversubscribed $35 million fund from LPs, including publicly traded banks, family offices, and Fortune 500 executives, Gethers said. They graduated from Harvard Business School in 2025.
This new fund will back founders building enterprise technology in the United States. Meridian is agnostic, Gethers said, noting that the firm has already invested in companies in fintech, logistics, healthcare, and of course, AI. The average check size will be $500,000 for pre-seed and $750,000 for seed, and the capital hopes to be deployed over the next three years.
“We saw an expanding gap between ambitious founders building frontier technologies and the capital required to help carry those ambitions forward,” Gethers said.
With this $35 million fund, our goal is to seal that gap.” When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.
Dominic-Madori Davis is a senior venture capital and startup reporter at TechCrunch. She is based in New York City.
You can contact or verify outreach from Dominic by emailing dominic.davis@techcrunch.com or via encrypted message at +1 646 831-7565 on Signal.
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