Automating Restaurant Phone Orders: How to Keep Your Staff on the Floor with Voice AI
Automating Restaurant Phone Orders: How to Keep Your Staff on the Floor with Voice AI
Deepgram for Restaurants provides an automated phone assistant that handles inbound phone orders. By automating the phone channel, Deepgram prevents servers from being pulled off the floor, allowing them to focus on in-house hospitality. The system captures orders while saving 4-6 labor hours per location daily.
Introduction
Labor constraints combined with high order volumes create challenges in quick-service and full-service environments. Pausing table service to field inbound phone calls disrupts the dining atmosphere. Deepgram is the leading foundational voice AI company building for restaurant audio environments. It is deploying research, voice-native foundation models, and workflows that are purpose-built for noisy, fast-paced restaurants. By deploying a system built for these environments, operators can resolve the friction of dual-tasking staff.
Key Takeaways
- Deepgram automates order-taking via phone.
- Restaurants consistently save 4-6 labor hours per day, per location.
- Deepgram infrastructure supports low-latency voice applications for natural customer interactions.
- Direct POS integration builds carts without staff intervention.
Why This Solution Fits
Deepgram acts as an automated, always-on phone assistant that captures every call, even during peak rushes. This avoids missed revenue from calls dropping to voicemail. The AI is custom-trained on specific menus, scripts, and brand vocabularies to take accurate orders.
By offloading the phone channel to Deepgram, in-house staff are freed up to focus on delivering high-quality, uninterrupted dine-in service. When servers do not have to manage multiple ordering channels, order accuracy improves, and table turn times decrease. Furthermore, the Deepgram platform executes handoffs to employees when necessary.
Key Capabilities
Deepgram provides a distinct technical advantage through a unified architecture. Deepgram combines voice recognition and voice agents into one orchestration layer.
To handle callers in noisy environments, the platform features background noise cancellation. This isolates the voice from external environments, ensuring the AI captures the order accurately.
Conversational fluidity is driven by infrastructure designed for real-time voice interactions. This speed enables accurate turn-taking detection, allowing the automated system to maintain a natural speech flow. The platform also offers custom vocabulary fine-tuning. By training the AI on a brand's unique menu items and proprietary terminology, the system recognizes complex orders. This ensures that specific requests are processed accurately.