The Israeli video personalization company is launching Strata, a basic model that reportedly creates separate, editable layers for text, animation, footage and actors instead of a single flat file. It represents a direct challenge to the architectural limitations of diffusion-based video generators.
Every AI video model currently on the market produces the same thing: a flat file. You can view it, share it, and crop it around the edges, but if you want to change the font, adjust an animation, or swap out the background, you’re basically starting over again.
This limitation has kept AI video out of professional production workflows where video was always created in layers, with separate tracks for text, motion graphics, footage and audio that can be adjusted independently until final rendering.
Idomoo, the Israeli corporate video personalization company, today announces Strata, a generative AI foundation model that it claims is the first model designed specifically for multi-layered video output. Instead of generating pixels, as Idomoo co-founder and CTO Danny Kalish puts it, Strata generates structure: independent layers of typography, animation, motion paths, and synchronized audio, all assembled into what the company calls a “production-ready video draft.”
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The difference is architectural. Standard diffusion models combine everything into a single tensor during generation; The spatial and temporal relationships between elements are baked into the pixels themselves.
According to Idomoo, Strata solves a different computational problem: it designs the entire composition, defining placement, contrast, movement, timing and pacing at all levels simultaneously, while enforcing brand guidelines. The resulting output can be edited at the layer level, just like a professional would work in Adobe After Effects.
Strata is part of Lucas, Idomoo’s AI video agent, which builds on the company’s existing next-generation video platform. One of his more technically specific skills is brand awareness: Lucas analyzes a company’s approved content to extract what Idomoo calls brand DNA, which includes design, narrative and assets.
Strata then applies this specification to every video generated through the platform, enforcing typography, motion cues, color values and tone of voice throughout the output at scale. The intent is to eliminate the template workaround that most “AI wrapper” products currently rely on, where generated footage is limited to preset layouts.
Idomoo’s argument is that forcing content into templates results in a noticeable visual compromise; Instead, Strata designs individual blueprints for each video.
Personalization is the other axis. Because Strata’s output is layered rather than flat, individual data fields, names, account details, transaction histories and product images can be inserted into specific layers of the video composition in real time.
This is the core of Idomoo’s existing business model: the company’s platform already serves JPMorganChase, Verizon and American Airlines, among others, and generates personalized videos at scale for customer communications, onboarding and marketing.
Strata theoretically makes this personalization much more sophisticated because it occurs at the composition level rather than as an overlay on top of a pre-rendered clip.
The company is cautious about the scale of the launch. An early access version is currently being tested by several of its largest customers. It is available now via Lucas AI Video Agentbut Idomoo has not disclosed which customers are in the early access cohort, what benchmarks the model was tested against, or how it compares to standard diffusion models in terms of quality metrics.
The claim of “first base model specifically designed for layered video” is Idomoo’s own formulation and has not been independently evaluated. The Strata technology is patent pending.
It’s worth noting that Idomoo’s own platform documentation has so far explicitly stated that it uses standard AI base models rather than proprietary models. Strata represents a significant shift in this positioning: from a company applying AI to video to a company building foundational AI for video.
Whether the underlying architecture meets this framework will become clearer as enterprise customers move from early access to production deployments.
Founded in 2007 by Yaron Kalish, Danny Kalish and Assaf Fogel, the Ra’anana-based company has raised a total of $27 million, including a $9 million Series A in 2013 and an $18 million Series B in 2019. The company has been building its personalized video platform for enterprise customers for nearly two decades, giving it an unusual amount of structured video production data which it can train.
