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Two restaurant brands at opposite ends of the spectrum: one sells sweet treats, the other sells fried chicken combos. Their menu logic is nothing alike, and both are valued Deepgram customers.
That distance between the two brands is the whole challenge of enterprise voice AI. No two deployments look alike, because no two menus or POS systems do. A rollout across thousands of locations carries thousands of these problems.
That's why the biggest brands should build and own the answer. Direct access to research teams that write AI models – like Deepgram Labs – is what will separate truly forward-thinking brands apart in an AI-led future.
One sells chicken, one sells sweets, and neither is simple
A key customer of Deepgram for Restaurants is a publicly traded fried chicken restaurant. Its menu maze is every variation of chicken combo meals, sides, and sauces you can think of. It's live in stores now on Oracle Symphony POS.
Another key customer of ours is a publicly traded pastry brand with more than a thousand shops, with more menu complexity than you might initially think. A custom box is a dozen separate decisions. Add a steady stream of limited-time flavors, and the agent has to know what "that blue donut from the commercial" is the week it airs. It's already live across a healthy slice of their locations, taking orders by drive-thru, phone, and catering, integrated with their Aloha POS.
Two problems, two speeds, one set of models we own underneath both.
What they're actually buying
These brands are injecting voice AI into the veins of their company. From Deepgram, they’re buying the voice layer underneath everything, not a single bolt-on feature. We own the models themselves: speech-to-text, text-to-speech, and speech-to-speech. We wrap them in the parts a voice agent needs: noise filtering for the background noise and the blown speaker, a live menu the agent reads from, cart building logic, routing, evals, sentiment on every order, and way more. They get a forward-deployed engineer and models fine-tuned on their own menu and audio, so their teams build on something instead of assembling it.
It also reaches well past AI ordering. The same voice layer takes phone calls for reservations, runs the kiosk and the web, and handles staff interactions in the back, so the whole operation moves through voice AI, not just the lane outside.
Why enterprises should build AI for themselves
The future of software is BYO. Tools like Claude Code enable engineers to build stuff they couldn’t before, and it’s only going to get easier by the month. Brands that can work directly with model providers to build for themselves, should.
These two brands chose Deepgram for Restaurants because of how we’re enabling the builders: the frontier models, the custom fine-tuning, the restaurant-specific capabilities, the orchestration. Our engineers show up at the validation store to get the first deployments right, take the research and integration risk off their plate, and enable enterprise engineers to own the outcome (and the margins).
If you're rolling out voice AI across 1,000+ restaurant locations and want a slice of the future of AI, let's talk.
