Generative Media is Rippinggg
fal has raised $1.65B in combined Series E & Series F funding, with Sequoia Capital leading the E & Bessemer Venture Partners leading the F. Its founders see generative media as 1 of only 3 product market fits in AI, alongside search + coding agents.
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Co-founders Burkay Gür (CEO) & Gorkem Yurtseven (CTO) started fal in 2021 after building machine learning infrastructure at Coinbase and Amazon. fal runs the infrastructure behind image, video, audio, and 3D models, serving developers, studios, and the model labs themselves.
Recorded at Dalida in San Francisco, Burkay and Gorkem explain how fal moved from Python data infrastructure into generative media, why video and image now split its revenue 50/50, and how demand kept rising as video prices jumped more than 10X. They also cover fal’s 150+ person org with only 2 reporting levels, the compute shortage shaping model launches, and why they believe the margin in AI sits with compute providers over applications.
“AI really has 3 product market fits. One of them is search. The other really clear one that’s growing really fast now is coding agents. And the third one is, we believe, generative media.”
We cover:
› The $1.65B Series E & F
› Why individuals spend $10K to $20K a month on generative media
› Veo 2 pricing and the shift to professional ads and film work
› Super ICs and hiring for agency, hunger, and humility
› World models, open source, and Hollywood adoption
𝐓𝐈𝐌𝐄𝐒𝐓𝐀𝐌𝐏𝐒
(00:00) Burkay Gur & Gorkem Yurtseven, Co-Founders at fal
(00:48) Why fal stopped chasing headlines
(03:15) Why generative media is AI’s next big market
(04:51) The infinite demand for AI videos
(09:35) The future of AI-generated ads
(13:19) How fal pivoted into generative media
(18:02) Hiring people who live and breathe AI
(23:01) Where AI meets Hollywood
(24:29) From friends to Co-Founders
(27:48) What a “Super IC” actually is
(35:58) The hardest part of staying at the frontier
(37:42) Why compute is the bottleneck for new models
(41:55) Why AI models have such weird names
(43:56) The story behind the name fal
(45:12) Why open source isn't going anywhere
(49:02) "AI has had zero impact on Hollywood"
(53:39) Waiting for AI's Toy Story moment
(56:58) Why Jack Dorsey is underrated
(58:55) Why the application layer has no margins
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fal Raises $1.65B Across Combined Series E & Series F
Sequoia Leads the Series E & Bessemer Leads the Series F
fal has raised $1.65B in a combined Series E and Series F. Sequoia led the Series E and Bessemer Venture Partners led the Series F.
Sequoia also led fal’s $140M Series D at a $4.5B valuation in December 2025, which followed a $125M Series C led by Meritech in July 2025. Bessemer has been an investor since the $49M Series B in February 2025.
fal runs inference for image, video, audio, & 3D models, serving developers, studios, enterprises, and the model labs that build the models. Burkay Gür (Co-Founder and CEO) and Görkem Yurtseven (Co-Founder and CTO) founded the company in 2021 after working on machine learning infrastructure at Coinbase and Amazon. The company has about 150 employees.
Gür said the company has moved away from publicizing each round.
“As you do more rounds, I think it’s irrelevant. It’s the business that matters more.”
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Dalida, Turkish Coffee & the 2 Meanings of fal
The interview was recorded at Dalida, an Eastern Mediterranean restaurant in San Francisco with Turkish influence, run by chefs Sayat and Laura Ozyilmaz. Both founders are Turkish, and Yurtseven got married at Dalida with Gür officiating.
The name fal carries 2 meanings:
It is an acronym for Features and Labels, 2 terms from machine learning that predate the current AI wave.
“If you’re a real OG, you would know those 2 terms.”
fal is also the Turkish word for a fortune read from the grounds left in a cup of Turkish coffee, a practice common across Turkey. The founders describe that meaning as a prediction of the future.
fal
/faɫ/ · noun · Turkish
Pronounced approximately “fahl” (rhymes with doll in many American accents)
Definitions
Fortune-telling; divination. The practice of predicting future events, particularly through interpreting coffee grounds, cards, or other symbols.
Fortune; fate; luck. A person’s destiny or prospects.
Omen; augury. A sign interpreted as indicating what may happen in the future.
Generative Media as 1 of 3 Product Market Fits in AI
Gür groups AI into 3 product market fits. The first is search, starting with ChatGPT and now including Google and Gemini. The second is coding agents. The third is generative media.
Coding and generative media are the only 2 categories where an individual user spends $10K to $20K a month. In generative media, that user is a professional at an AI-native or traditional studio generating video full time.
“AI really has 3 product market fits. One of them is search. The other really clear one that’s growing really fast now is coding agents. And the third one is, we believe, generative media.”
“This is the only other use case in AI that an individual can spend that much money.”
Video & Image Now Split fal’s Revenue 50/50
Video grew from 0 to roughly 70% of fal’s revenue after video models arrived. Image editing models then pulled image usage back up, and the split is now 50/50.
Image editing also feeds video work. Users generate keyframes with image editing models and video models interpolate between them.
“Turns out image editing models brought life back to image models, and then it’s also useful for video models as well because you can create different frames, and video models does such better job interpolating between those frames.”
The best current video models generate 10 to 12 seconds per clip, with newer models expected to reach about 30 seconds. Gür said cost rises exponentially with resolution and duration because inference requires more attention and more pixels, and he expects spend to keep climbing until models can stream real-time, high-definition video.
Video Prices Rose More Than 10X & Demand Followed
Early video models from Kling and MiniMax launched at roughly 40 cents per 5-second clip and settled near 30 cents. Google’s Veo 2 launched at $5 per 5-second clip, and more expensive models followed.
Yurtseven said the higher quality moved usage into professional work, including advertising, marketing, and film production.
“Veo 2 was very surprisingly $5 per 5-second video. So it jumped more than 10X. And we were like, ‘Who the heck is gonna pay all this money?’ Turns out there is essentially infinite demand.”
fal also hosted OpenAI’s Sora and saw volume grow sharply in the 3 months before it was taken down because of it’s expensive compute demand.
Ads Lead Near-Term Demand, With Robotics Emerging
Gür sees user-generated-style ads as a strong fit for current video models. Lighting and polish matter less in that format, longer ads can be built from short cuts, and engagement data from posted ads can drive automated iteration.
“The content is usually throwaway. If it doesn’t work, make a new one.”
Yurtseven said some creators and large companies already run this testing loop, and he expects it to become standard within a few years.
Outside of ads, Yurtseven pointed to physical AI. Black Forest Labs worked with robotics company Mimic to apply the backbone of its latest Flux model to robotics, using the model’s learned physics to generate synthetic training data.
From Python Compute to Generative Media
fal’s original 2021 thesis was data infrastructure. The founders saw Snowflake and Databricks as compute owners running SQL in the cloud and set out to do the same for Python data science and machine learning workloads.
After Stable Diffusion, DALL-E, and ChatGPT, the 5- to 6-person team skipped the open source language model market, where token prices were falling below cost. It focused on running image models faster on its existing infrastructure.
“With this other business, we ran it for a year, we didn’t make a single dollar. With this one, our revenue’s starting to go like this. There’s clearly something here.”
Within 3 to 6 months, the team expected the category to serve different buyers from LLMs, mainly in ads and marketing. It coined the term “generative media” and put it on its website, and for the first few years had to explain what it meant.
The Storefront, fal Design Lab & a Storyteller Hire
“Every big company is gonna be a compute company. Just the storefront is gonna be different. Our storefront is unique and interesting. No one else has a storefront similar to us.”
Gür said compute is what drives revenue across AI companies, whether the front end is a coding agent, a data platform, or a neocloud with no storefront at all. fal’s storefront is generative media, and the company has put it on San Francisco’s streets.
The billboard campaign runs on painted building walls and an Outfront billboard. The main creative reads “Your creativity layer” with video, image, and audio icons under the tagline “Build, deploy, train on fal.ai,” in 3 colorways. A second execution pitches fal Serverless as inference for generative media. The campaign was designed in-house at fal design lab with Hyun Jung Lee.
fal also built a storytelling role into the team, recruiting with an open call.
“if you’re a “storyteller”, “narrative strategist”, evolved comms human etc. in sf, dm me.”
fal hired Michelle Wu as its Storyteller, and Marketing Lead Tina Sang hosts long-form conversations on creativity in AI through fal Studios.
fal Sits Between Model Labs & Applications in a Compute Shortage
fal works as an infrastructure partner for model providers and as the API layer for applications and studios. Gür said labs now need inference capacity lined up before launch, and many partner with fal to secure it.
“If you are coming up with a new model, you really have to plan ahead of time. You have to make sure you have enough compute to run inference.”
Customers often time their own product releases to new models. fal forecasts that demand and procures compute ahead of it so capacity does not go entirely to coding agents.
Yurtseven said the category has more labs and more leapfrogging than LLMs, across image, image editing, video, 3D, and speech. Gür attributes part of that to training data supply.
“There is so much video data out there and so much new video data is being produced every day that no one claims to train all of that data.”
150 People, 2 Reporting Levels & Super ICs
fal has at most 2 levels of reporting and no pure managers. Teams form around senior individual contributors who both build and lead, a structure Yurtseven calls super ICs.
“Basically you want your management layer to be super ICs. So people who are just so epic at their job, they can actually do hands-on work. And then they can also lead teams.”
Gür expects the structure to hold as long as coding agents keep improving, with each technical leader supervising 5 to 10 engineers. Yurtseven estimates coding agents make fal’s engineering team 3 to 4X faster, meaning fal would need roughly 4 times the headcount without them.
Hiring screens for agency, hunger, and humility. Engineers are expected to work directly with customers and make business decisions. Gür, who joined Coinbase in 2016 at about 100 employees, cited its crypto knowledge quiz as the model for hiring people already obsessed with the field.
“If you didn’t hire them, they would be doing this anyways.”
Candidates are told to expect 60- to 80-hour weeks during crunch periods. The team generally does not work weekends.
» » » » fal is hiring!! « « « «
Hollywood, IP & Open Source
Gür said Hollywood business has grown over the past 6 months to a meaningful share of fal’s revenue, while labor impact has been close to 0.
“So far I would say AI had zero impact on anything in Hollywood. The business we get from Hollywood has been increasing in the last 6 months. But I would say it had zero impact on the labor.”
Legal review has slowed studio adoption alongside model quality. Studios want open source models they can fine-tune with LoRAs for lighting, unreleased characters, and house styles.
Gür expects labs that fall behind to keep open sourcing models for distribution. fal now runs both open and closed models, and enterprise customers place more trust in the process when they know inference runs on fal’s GPUs, since unreleased content is often a model input.
World Models & Timeless Content
Yurtseven said world models, which let users navigate a generated environment with keyboard inputs, went from unusable to compelling in about 3 months. Newer architectures keep objects persistent when the user looks away and back.
“You’ll be able to actually build a game with a prompt, which I didn’t believe in literally 3 months ago, but I think that space is just gonna blow up.”
He sees AI gaming as a possible 4th product market fit, constrained by the need for a GPU running for each player.
Gür expects the first widely accepted AI short film or animation within 12 months that audiences still enjoy years later, comparing it to Toy Story for computer graphics.
Hot Takes on Margins & Compute
Gür said the early consensus that margin would accrue to the application layer has reversed, with application companies now spending heavily on marketing against heavy competition.
“Margins are close to zero in the application layer. There’s so much competition. People need to spend so much money for marketing. You can only create margin if you are in the compute path.”
He expects every large AI company to become a compute company with a different storefront, whether coding agents, data platforms, or generative media.
Yurtseven speculated that an OpenAI and Meta merger would make sense given each company’s position in consumer and enterprise, noting he has no information on it. He also said coding is becoming part of generative media as developers on fal build programmable video and richer applications.
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