Seattle-based retail tech provider Augmodo this week announced that it has secured $37.5 million. The round was led by TQ Ventures, with participation from existing investors Lerer Hippeau, NewFare, WIN, and Interlace. New investors in the round include Arena Holdings and Jefferson River Capital.
So what does Augmodo do, and what attracted the latest funding? The company calls itself “a real-time inventory and task tracker using spatial AI to improve efficiency and convenience for retailers, brands, and consumers.” That’s a mouthful, so let’s break it down in English, especially the spatial AI part.
Augmodo’s core value resides in its SmartBadges. These are cameras worn by retail associates as a lanyard. From that vantage point, the badges assemble 3D maps of store interiors. As associates wander store aisles to do their thing – stocking, helping customers, etc. – the badges scan the environment.
Those scans then become the foundation for everything else Augmodo does. For example, its spatial AI assistant is a store-facing tool that recommends optimal layouts, helps identify out-of-stock inventory, and automatically orders products accordingly. Many productivity use cases will flow from there.
Holy Grail
All the above can be compared to how autonomous vehicles work. By scanning their environments – along with cumulative scans from other vehicles – they can better understand the road. Augmodo claims that its passive scanning method is 10x more effective and 100x cheaper than robotic interior scans.
Those cost advantages make sense because the approach piggybacks on store associates’ existing movement. This philosophy was inspired by the way Pokémon Go players collectively and passively scan environments to make the game better. In fact, Augmento founder Ross Finman is a former Niantic exec.
But the real idea for Augmodo came from a personal struggle that Finman experienced. During the 2022 baby formula shortage (which this author also lived through), he drove hundreds of miles to find the needed supplies. Held back by a lack of inventory transparency, he knew there had to be a better way.
That anecdote previews other potential applications for Augmodo’s foundational data collection. Though the use cases outlined above are store-facing – which is a prudent place to start – customer-facing product search could be the real endgame. It’s all about making store aisles searchable.
In fact, this vision of searchable stores has been a holy grail in the world of local search for the past two decades. The value proposition to find out exactly what’s on the shelf at nearby stores has taken various forms – from text search to fancier in-store wayfinding (think: Google Maps for your shopping list).
Scalable, Sticky & Monetizable
Sticking with the simpler and more prevalent text search format, players such as Krillion, Milo (acquired by eBay), and a few others have historically assembled point-of-sale (POS) data to come fairly close to bringing this vision to life. Google Shopping has also come close, but no one has perfected it.
Beyond tapping into the right data sources, the reality of a quickly changing world throws a wrench into things. In other words, consumer-facing real-time information about what’s on the shelf at any given moment remains an unsolved problem. Whoever can make this happen will see a long-awaited payoff.
That brings us back to Augmodo. With its elegant ways to constantly scan store aisles, the data could be refreshed faster than traditional methods, such as tapping into POS systems. And if it is a better mousetrap, Augmodo could spin out APIs, so that other local search apps can tap into the data.
That last part is our speculation, but would make Augmodo’s tech more scalable, sticky, and monetizable – which likely influenced the latest cash infusion. Meanwhile, Augmodo could face challenges in the immense BD task of forming retailer partnerships at scale. That’s the part we’ll be watching closely.
Header image credit: Franki Chamaki on Unsplash
