Liquid Interactive Launches Liquid Photos With AXL Funding
Liquid Interactive emerged from stealth on July 28 with its Liquid Photos consumer app and C$700,000 in backing from Toronto venture studio AXL, BetaKit reports. Co-founded by Maple Scan creators Sasha Ivanov and Ben Pearman, the startup uses generative AI to turn selected camera-roll photos into interactive visual experiences. Dealroom reports that a later product, Liquid Studio, is intended for brands, agencies, and creative teams.
Liquid Interactive emerged from stealth on July 28 with Liquid Photos, a consumer app that turns selected camera-roll images into interactive visual assets, and C$700,000 in backing from Toronto venture studio AXL, according to BetaKit.
The startup was co-founded by Sasha Ivanov and Ben Pearman, who previously co-founded the grocery-scanning app Maple Scan. Dealroom identifies Ivanov as chief executive officer and Pearman as chief technology officer, and reports that both worked at AXL before spinning the venture out.
From static images to explorable media
BetaKit reports that Liquid Photos can use photos captured at the same place and time to create a spatial experience that users can rotate in three dimensions, despite the source images being two-dimensional. The product can also separate an object into visual components for navigation. Dealroom describes examples including reconstructing a hiking trail from a photo sequence, exploring the inside of an object without a 3D scan, and asking questions about images in an album.
Ivanov told BetaKit that text-based chat is less engaging than video-based social experiences: "When we compare [text chatting] to other experiences online and in our lives, like video-based platforms on social media, it's a lot less engaging and interesting. There's a lot we're losing when we stick to text only."
BetaKit reports that Liquid Interactive is developing patented technology for interactive photos, online demonstrations, and other visual assets. The sources differ on product availability: Dealroom reports that the app is available as a free download, while BetaKit reports that the company hoped to launch on the App Store soon and references Apple and Android users. The retrieved reporting does not resolve that discrepancy.
AXL-backed product roadmap
According to Dealroom, Liquid Photos is the first of several products based on the same technology. It reports that a second product, Liquid Studio, is intended to let brands, agencies, and creative teams turn product imagery into custom interactive experiences.
Daniel Wigdor, AXL co-founder and CEO, framed the investment as a bet on new interfaces for AI. "The companies that matter from here won't be the ones with the biggest model. They'll be the ones that invent new ways for people to interact with it," he told Dealroom. In a separate quote published by BetaKit, Wigdor said, "The way we actually use [AI] has barely moved, and history says whoever closes that gap is who defines the era."
For ML product teams, the launch is a small but concrete example of a broader interface question: multimodal models can interpret and generate visual content, but product value often depends on interaction design, rendering quality, latency, and reliable handling of incomplete image sets. Companies pursuing comparable visual-first experiences typically need to combine model output with conventional graphics, media-processing, and mobile application infrastructure.
Key Points
- 1Liquid Interactive launched Liquid Photos with C$700,000 from AXL, applying generative AI to camera-roll images rather than text-only prompts.
- 2The product demonstrates a visual interaction pattern where two-dimensional photos become spatial, explorable media through AI and interface design.
- 3Comparable multimodal products often depend on graphics pipelines, low latency, and robust media processing alongside model capabilities.
Scoring Rationale
This is an early-stage Canadian AI startup launch with modest pre-seed funding, not a new foundation model or broadly deployed platform. It is relevant to practitioners because it offers a concrete product-direction example for multimodal, image-centric AI interfaces.
Sources
Public references used for this report.
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