How Layer Accelerated Gaming Innovation with fal

Industry:
Gaming & Interactive Media
Use-case:
Generative AI infrastructure for game art, playables, and marketing creative across image, video, 3D, and audio
Results:
Accelerated model deployment, reduced GPU costs, and freed engineering resources, allowing a lean team to expand from game art into playables and marketing creative.
At a glance
24hrs
New model deployments to studios after request
2x faster
Inference speed compared to in-house clusters
30% lower
Infrastructure cost vs self-managed GPUs
300+
Game studios creating with Layer

Background

Layer is the one-stop creative platform for game studios, with more than 400 AI models in one workspace for game art, playables, video ads, and marketing creative. Take-Two, Zynga, King and 300 other studios use Layer to ship on-brand content at the pace live games demand.

The Challenge

Every format a studio asks Layer for depends on having the right model. A playable ad, a localized campaign, and a set of 3D assets each draw on different image, video, 3D, and audio models, and new ones arrive constantly. Layer started on its own GPU clusters, which ran at low utilization and turned every new model into an infrastructure project for a small team.

The Solution

With inference on fal, a new model reaches Layer's studios within 24 hours of a request. That speed is what let Layer grow beyond game art. Playables built from a store link or gameplay clip, campaigns spun out of a single key art, and trailers cut from existing game assets all combine several models, and each new one is in Layer's workspace as soon as it launches.

“We credit our switch to fal in our ability to build the best product for gaming while having the lowest amount of money raised and the smallest team. The agility is everything. fal let us compete with providers much bigger than us and still win.”
Volkan Gurel, CEO and Co-Founder, Layer

The economics changed too. Inference runs 2x faster than on Layer's in-house clusters at 30% lower cost, which matters when a studio generates dozens of ad variations to find the one that performs. And instead of operating GPUs, Layer's engineering team focuses on the Layer platform.

“We don’t want to manage GPUs. We want to solve business use cases for game studios. fal enables us to stay focused on that mission.”
Volkan Gurel, CEO and Co-Founder, Layer
Customer Highlights
Quora
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A key part of this strategy involves seamlessly integrating the latest image and video generation capabilities into the user experience. The ability for users to quickly create and share visual content unlocks new opportunities to explore what's possible and democratize content creation, making AI more engaging and practical.
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Genspark and fal
fal enabled Genspark to rapidly scale from prototype to production, eliminating infrastructure overhead and empowering their team to focus on building next-gen agent workflows.
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Bria needed to bring new models to market faster while expanding developer adoption
Bria partnered with fal in 2024 to make its models accessible to developers through fal's inference infrastructure and model marketplace. Today, Bria's engineers can take a model from research-ready to publicly available in days rather than weeks, without managing the underlying GPU infrastructure.
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How Layer accelerated gaming innovation with fal
Accelerated model deployment, reduced GPU costs, and freed engineering resources—allowing Layer to deliver world-class creative tools for game studios while maintaining a lean team.
Read more

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