While most AI video tools generate static content in seconds, Decart is building the infrastructure to make high-fidelity video generation happen in real-time, opening the door to live interactive experiences that could reshape gaming, streaming, and social media. The Israeli startup, founded in 2023, has identified a critical bottleneck in generative AI: the technology works well for one-shot outputs, but generating video or immersive experiences remains too expensive and too slow for live applications. Diffusion models, the underlying technology behind most AI video generators, typically require many seconds of computation to produce a single second of video, while interactive applications demand generation in under 16 milliseconds per frame.

Why Is Real-Time AI Video Generation So Hard?

The generative AI market is exploding. The global market is projected to grow from $103.6 billion in 2025 to $1.3 trillion by 2034, with generative AI in gaming alone expected to reach over $5.1 billion by 2030, up from $1.8 billion in 2025. Consumers are spending increasing time in interactive, media-rich environments like TikTok, Twitch, and gaming platforms, looking for tools that let them co-create in real time. Yet the technical infrastructure to enable that growing demand is severely lacking.

The core problem is inefficiency. Most AI-generated content is built for batch processing, where you submit a request and wait for output. Generating video or immersive experiences remains prohibitively expensive and slow. Inefficiencies in how hardware is used mean real-time generation remains largely out of reach for most applications. This is where Decart enters the picture.

How Does Decart's Approach Differ From Competitors?

Decart's core innovation is an inference engine that drastically improves GPU utilization for generative media models. Rather than building new AI models from scratch, the startup focuses on optimizing how existing models run on hardware. This engineering-first approach yields order-of-magnitude efficiency gains. The company claims its world models run 10 times more efficiently than alternatives, and its stack cuts the cost of GPU-based video generation from hundreds of dollars per hour to cents.

As of August 2026, Decart's product stack has three layers designed for live-stream and interactive use cases:

• DOS: An inference-optimization layer sold to enterprises that improves how AI models run on GPUs
• Oasis: A world model that generates interactive environments without requiring a traditional game engine
• Lucy: A live video model that edits video streams as they run, enabling real-time video-to-video transformation

All three products share the same engineering premise: custom low-level optimization of how models run yields dramatic efficiency improvements. The company's stated mission is to make AI "fast, responsive and affordable enough to power dynamic, interactive experiences for millions of concurrent users".

Who Founded Decart and What's Their Background?

Decart was founded in September 2023 by Dean Leitersdorf (CEO), Moshe Shalev (Chief Product Officer), and Orian Leitersdorf (Chief Scientist). The founding team brought together complementary skill sets. Dean Leitersdorf is a Technion-trained computer scientist who completed his BSc, MSc, and PhD in computer science by age 23, earning an ACM dissertation award. His younger brother Orian completed a Technion doctorate at 22.

Moshe Shalev's path was markedly different. Raised in a Haredi household in Bnei Brak, he studied accounting while working as a butcher's assistant before volunteering for the Israeli Defense Force at age 23. Shalev spent 13 years in Unit 8200, Israel's elite tech-intelligence corps, where he built and led large AI infrastructure projects and even co-founded a nonprofit serving Israeli charities.

"We're both strong executors, but we dream differently," Shalev said of the partnership. "Decart is the meeting point between Dean's ability to imagine technology on a broad scale and my ability to bring it into an organization and operationalize it."

Moshe Shalev, Chief Product Officer at Decart

Dean Leitersdorf and Shalev first met in Israel's intelligence community in mid-2021 during a chance "hallway conversation" that sparked their partnership. Leitersdorf combined academic AI expertise with a product-minded vision, while Shalev brought operational and systems-building experience. They began recruiting AI researchers even while Leitersdorf was abroad and formally registered Decart in September 2023, coinciding with the arrival of ChatGPT and a wave of interest in generative AI.

How Did Decart Navigate Early Skepticism?

When Decart raised its seed round in mid-2024, the founders encountered mixed reactions from investors. About half were excited and ready to invest, while the other half praised the technology but said they didn't understand the end product. One investor, an anonymous female investor nicknamed "Sarah," openly doubted the venture, saying Israelis "don't know how to train models" and have missed the generative AI wave.

Rather than being discouraged, the founders took this as motivation. They hung a photo of "Sarah" on their office wall as a constant reminder to prove her wrong. The startup emerged from stealth with both an enterprise product and a consumer demo, and it began generating revenue immediately. The founders later summed up their mindset by saying they could have built something to sell off quickly, but instead they were determined to "build an app for a billion users," underscoring their long-term, ambitious outlook.

Steps to Understanding Decart's Market Opportunity

• Market Size Context: The global video game industry generated $189 billion in 2025 and served more than 3.6 billion players, while social and streaming platforms like TikTok and Twitch see billions of hours of user engagement each month, creating massive demand for interactive content tools
• Technical Bottleneck: Most AI video generation requires many seconds of computation per second of output, while interactive applications demand generation in under 16 milliseconds per frame, a gap that existing tools cannot bridge
• Cost Advantage: Decart's optimization approach reduces GPU-based video generation costs from hundreds of dollars per hour to cents, making real-time AI experiences economically viable at scale
• Organizational Expansion: As of 2026, Decart operates from Tel Aviv, San Francisco, and New York, with Kfir Aberman, a former senior research scientist at Google and principal research scientist at Snap, leading the San Francisco R&D center

The company's founders have contrasting personalities that shaped its culture. Leitersdorf, in his mid-20s, has high technological ambitions, while Shalev, in his late 30s with more leadership experience, brings a grounded business perspective. Leitersdorf "charges ahead with vision," while Shalev's "more grounded business mindset" keeps the company tethered to what can be executed immediately. Despite their age gap and very different backgrounds, the two found in each other a mutual trust and a shared hunger to make Israel a leader in AI.

Decart's emergence reflects a broader shift in how generative AI is evolving. As the market moves beyond static tools toward live, interactive environments, the infrastructure layer becomes critical. Companies that can optimize hardware utilization and reduce computational costs will unlock new use cases in gaming, streaming, and social media that are currently impossible with existing technology. Decart's focus on real-time performance, cost-efficiency, and interactivity positions it at the center of this transition.

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