Elorian, the Palo Alto artificial intelligence startup that raised a $55 million seed round at a $300 million valuation before launching a product, released its first model on Friday. The model, called Glimpse, is available as a research preview with API access. A chat interface is waitlist-only for now.
The company's pitch rests on a simple complaint: today's AI models, for all their skill with language and code, still struggle to really see. Most multimodal models look at an image once, convert it into tokens and reason about it in text, much like describing a photo from memory. Glimpse keeps returning to the source. Partway through its reasoning, it can crop into a region, pull specific frames from a video or run code to measure or compare what it is looking at. Elorian calls this a “visual scratch space.” It is roughly the same move a person makes when they pinch to zoom on a phone photo to check what they thought they saw.
Andrew Dai, a former Google DeepMind researcher who now serves as Elorian's CEO, says one of the clearest signs of the problem came during a game night. Last year he photographed a board game he had just finished playing with friends and asked a frontier model who was winning. It could not say.
Board games “each have their own visual language, each have their own iconography, symbols,” Dai told TechCrunch. “To an adult, it’s quite easy to understand what’s going on with minimal text, but these models aren’t able to intuit what the symbols mean.” He pointed to another example. “Humans can look at Ikea diagrams, with no text, and assemble Ikea furniture, right? Why can’t AI models?”
The crop-and-zoom technique is not entirely new. OpenAI added a version of it during reasoning to its o-series models in 2025. Elorian's argument is that it built the entire model around the approach, and did so cheaply. The company says a small team trained Glimpse on a few hundred GPUs and that the model is substantially smaller than the frontier systems it is benchmarked against.
Glimpse costs $0.60 per million input tokens and $3 per million output tokens. That puts it above lightweight models such as Haiku and Luna in price, but below mid-level models like Sonnet and Sol. Elorian's evaluations show Glimpse outperforming GPT-6 Astra on scientific chart reasoning and short-form video captioning, with competitive results on other visual reasoning tasks.
The company emerged from stealth six months ago with a funding round co-led by Striker Venture Partners, Menlo Ventures and Altimeter Capital. Nvidia and Google chief scientist Jeff Dean also participated. For now, Elorian is targeting companies that sit on large amounts of video, including robotics firms, scientific labs, media companies and creative businesses.
Elorian's longer-term plans go further. The company wants to move from seeing to doing, building a model of a scene and using it to choose an action. That could include directly controlling robots. Dai said Elorian aims to build “the world’s best visual reasoning model” next year, one that leads on every visual reasoning test.
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