TRAY and Maple Integrated Its AI Phone Ordering for Restaurant Chains
Adam Harrie — May 8, 2026 — Tech
References: businesswire
TRAY and Maple launched a joint integration bringing 24/7 AI phone ordering to multi-unit restaurant brands running on TRAY's POS platform. The restaurant AI phone ordering systems connect directly to TRAY's menu data, including items, modifiers, pricing and availability, and deploy in minutes, with orders landing instantly in kitchen display systems and receipt printers.
More than 40% of restaurant calls go unanswered during peak hours, costing a single location over $30,000 in lost phone orders annually. Since launching in December 2023, Maple has answered more than one million restaurant calls, resolving 96% without human intervention.
As multi-unit restaurant operators look for scalable solutions to front-of-house staffing gaps, TRAY and Maple show how integrating voice AI directly into an enterprise POS can capture missed revenue.
Image Credit: TRAY/Maple
More than 40% of restaurant calls go unanswered during peak hours, costing a single location over $30,000 in lost phone orders annually. Since launching in December 2023, Maple has answered more than one million restaurant calls, resolving 96% without human intervention.
As multi-unit restaurant operators look for scalable solutions to front-of-house staffing gaps, TRAY and Maple show how integrating voice AI directly into an enterprise POS can capture missed revenue.
Image Credit: TRAY/Maple
AI phone ordering in restaurants
Helps decide what restaurant tech to cover, who’s open to AI phone ordering, and which features matter most to drive visits or brand preference.
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When was the last time you ordered food by calling a restaurant?
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If a restaurant used an AI to take phone orders, how would you feel?
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Which AI phone-ordering feature would make you most likely to use it?
Trend Themes
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Voice AI Phone Ordering — Widespread deployment of conversational voice systems that handle entire order flows presents the potential to recover millions in previously lost phone revenue by automating peak-hour call volume.
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Pos-native AI Integrations — Embedding AI directly into point-of-sale data streams enables real-time synchronization of menus, modifiers and availability, creating opportunities for seamless end-to-end order accuracy and reduced operational friction.
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Autonomous Call Handling — High-resolution intent recognition and self-service resolution rates above 90% point to a shift where human staff are increasingly reserved for exceptions while routine interactions are fully automated.
Industry Implications
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Multi-unit Restaurants — Large restaurant chains stand to transform front-of-house economics as scalable AI ordering reduces dependence on shift staffing and captures missed revenue from unanswered calls.
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Point-of-sale Software — POS vendors can evolve into platform orchestrators by offering native AI modules that tightly couple commerce data with customer-facing automation, redefining value propositions to operators.
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Customer Contact Centers — Contact center providers could see their role shift toward supervising hybrid AI-human workflows as automated systems resolve routine inquiries and escalate only complex cases.
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