Everybody's building Voice AI for restaurants right now. Let's draw the map.

A year ago, you could count the serious Voice AI companies in restaurants on one hand. Now, there's a new funding round announced what feels like every other week, and the sea is filling up with fish, fast.

When a market booms so rapidly, it helps to draw a map. Here's how the restaurant Voice AI ecosystem looks from where we sit, which is the foundation layer, and what each group is working on.

A wave of companies productizes voice agents made specifically for restaurants. ConverseNow, Hi Auto, Arc, Presto, Maple, Loman, Vox, and Slang, are eight of them, and that list is nowhere near complete. Some answer the phone so a host or a line cook doesn't have to. Others run the drive-thru lane, tuning their agents to hold up against engine noise and complicated orders. They sell mostly to independents and smaller multi-unit chains, and they build the application layer: the personality, the upsell logic, the integration into the point-of-sale system. This group is growing and saturating at the same time. Some new entrant will raise a funding round most months, and the field is already crowded enough that a buyer can line up several vendors and compare them head to head.

The restaurant technology platforms want to bring Voice AI to the long tail of small and mid-sized restaurants already running on their systems. Toast, Olo, DoorDash, Grubhub, PAR, Glovo, and Yelp own the transaction and/or the merchant relationship, so their move is to make voice ordering a feature that any restaurant on the platform can turn on, across the drive-thru, the phone line, or an in-app ordering agent. Reach is the entire point. It is how voice ordering goes from a novelty to something a neighborhood pizza place runs without thinking twice about it. This group is normalizing AI adoption in their customers, while also building it into their own application layer. Voice-first interfaces are not far away.

The large chains are putting Voice AI into nearly every part of the operation at once: drive-thru and kiosk ordering, phone ordering, in-store assistants running on employee headsets, call center automation, and more. Taco Bell, Krispy Kreme, Starbucks, Burger King, Popeyes, Wendy's, and others are all building or piloting voice across one or more of these channels. The pressure behind it is the margin doomspiral, labor costs climbing while traffic stays soft, and automation is one of the few levers these chains have that doesn't mean raising prices again. Rolling it out across thousands of locations is hard, and they are doing the unglamorous work of making it run in production.

Underneath all of this is the same hard problem: understanding a human voice, with a heavy Boston accent, through a crackly speaker, with a diesel engine idling and a toddler melting down in the back seat. That layer is where Deepgram lives, and our aim is to reach every group on this map with what they actually need.

For the enterprise chains, that means giving their engineering teams the foundational speech and voice models to build their own solutions in-house, on their own terms, with the deployment and engineering support, reference architecture, and custom models to do so. For the restaurant technology platforms, it means two things at once: the models to build voice features they can market to their customers, and voice-native infrastructure running underneath their own products. For the Voice AI developers, it means frontier speech and voice models to build their agents on, so they can spend their energy on the product instead of the plumbing.

A healthy stack needs a solid foundation, and we'd rather the whole market succeed on top of one. Whether you're building Voice AI for restaurants, buying it, or running it across a few thousand locations, the layer underneath is the part we obsess over. And we’re the only foundational Voice AI provider laser-focused on restaurants. Let's talk.