Automating Orders with Voice Technology

Voice-first ordering just became real. Starbucks and Deepgram built a drive-thru prototype that handles 5+ modifications in pure chaos. Here's why this changes everything for quick-service restaurants: Drive-thru ordering is one of the most technically challenging environments for voice AI. You've got diesel engines running 6 feet from the microphone. Wind gusts hitting the speaker. Passengers shouting modifications from the back seat. These are the conditions that cause traditional voice systems to fail or require multiple repeats. The Starbucks prototype handles what breaks most voice AI: real-time complexity. The system processes every modification correctly. Then when the customer says "Actually, make that hot instead of iced" - it adjusts without restarting the conversation. This on-the-fly modification capability is what makes it revolutionary. Current drive-thru ordering breaks under pressure. During peak hours, staff juggle taking orders, handling payment, and coordinating with kitchen. This leads to order errors requiring remakes, frustrated customers leaving the line, and revenue loss when wait times exceed 5 minutes. Voice AI systems eliminate these bottlenecks through consistent throughput. The system processes orders at the same speed. It doesn't slow down, doesn't make more errors under pressure, and doesn't need breaks when volume spikes. But throughput is only part of the breakthrough. The system integrates with customer history and preferences. It remembers your usual order, suggests modifications based on past purchases, and handles loyalty programs without feeling transactional. Consumers now expect this everywhere. They want their preferences remembered, suggestions based on history, and zero friction at checkout - expectations that human-only drive-thrus struggle to meet consistently. The Starbucks prototype isn't an isolated experiment. Every quick-service restaurant faces identical operational challenges: noise interference, order complexity, peak demand pressure, and staff limitations during rush periods. The economics favor rapid adoption. Voice AI systems don't require breaks or call-outs. They maintain the same accuracy whether processing the first order of the day or the 500th. One system handles multiple concurrent orders across locations. The prototype proved this works in production conditions. But moving from prototype to scaled deployment requires infrastructure most companies lack: noise robustness that handles real chaos, real-time processing without latency, and integration that works across POS systems. This is what we built Voice.ai to solve. Our platform provides the noise robustness, cross-system integration, and scalable throughput that turns prototypes into production-ready voice ordering systems. If you're building in food service, retail, or high-throughput ordering environments, we should talk. If you're investing in companies tackling these problems, we should talk.

𝗦𝗾𝘂𝗮𝗿𝗲 𝗷𝘂𝘀𝘁 𝗴𝗮𝘃𝗲 𝗿𝗲𝘀𝘁𝗮𝘂𝗿𝗮𝗻𝘁𝘀 𝗮 𝟮𝟰/𝟳 𝗽𝗵𝗼𝗻𝗲 𝗵𝗼𝘀𝘁 — 𝗽𝗼𝘄𝗲𝗿𝗲𝗱 𝗯𝘆 𝗔𝗜 🍔📞 Square (Block) rolled out 𝗔𝗜-𝗽𝗼𝘄𝗲𝗿𝗲𝗱 𝘃𝗼𝗶𝗰𝗲 𝗼𝗿𝗱𝗲𝗿𝗶𝗻𝗴 so restaurants don’t miss another call at peak rush. The bot answers the phone, understands menu questions (“𝘞𝘩𝘢𝘵’𝘴 𝘨𝘭𝘶𝘵𝘦𝘯-𝘧𝘳𝘦𝘦?” “𝘌𝘹𝘵𝘳𝘢 𝘴𝘱𝘪𝘤𝘺, 𝘯𝘰 𝘥𝘢𝘪𝘳𝘺”), takes the order, and injects it straight into POS/kitchen – no staff juggling, no sticky notes. Early rollouts land alongside upgrades to Square AI (their conversational assistant) and an 𝗶𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗲𝗱 𝗕𝗶𝘁𝗰𝗼𝗶𝗻 𝘀𝗼𝗹𝘂𝘁𝗶𝗼𝗻 𝗳𝗼𝗿 𝘀𝗲𝗹𝗹𝗲𝗿𝘀.  — 𝗪𝗵𝘆 𝘁𝗵𝗶𝘀 𝗺𝗮𝘁𝘁𝗲𝗿𝘀 • 𝗡𝗲𝘃𝗲𝗿 𝗺𝗶𝘀𝘀 𝗿𝗲𝘃𝗲𝗻𝘂𝗲: Every call gets answered, even during dinner rush or short staffing.  • 𝗛𝗶𝗴𝗵𝗲𝗿 𝗼𝗿𝗱𝗲𝗿 𝗾𝘂𝗮𝗹𝗶𝘁𝘆: The system can confirm modifiers, allergens, pricing, and promos before firing to the line.  • 𝗖𝗹𝗲𝗮𝗻𝗲𝗿 𝗼𝗽𝘀: Orders land in the Square POS and kitchen display with audit trails; no rekeying = fewer errors.  • 𝗕𝗲𝗻𝗰𝗵𝗺𝗮𝗿𝗸𝗲𝗱 𝘁𝗿𝗲𝗻𝗱: Voice AI is spreading across QSR – the winners pair accuracy with tight POS integration. Square’s move brings that to independents and multi-unit locals. 𝗪𝗵𝗮𝘁 𝗲𝗹𝘀𝗲 𝘀𝗵𝗶𝗽𝗽𝗲𝗱 – Square AI gains deeper “𝗻𝗲𝗶𝗴𝗵𝗯𝗼𝗿𝗵𝗼𝗼𝗱 𝗶𝗻𝘀𝗶𝗴𝗵𝘁𝘀” (weather, events, reviews) to help with staffing and menus. – Square Bitcoin lets U.S. sellers 𝗮𝗰𝗰𝗲𝗽𝘁 𝗕𝗧𝗖 𝗮𝗻𝗱 𝗲𝘃𝗲𝗻 𝗰𝗼𝗻𝘃𝗲𝗿𝘁 𝗰𝗮𝗿𝗱 𝘀𝗮𝗹𝗲𝘀 𝘁𝗼 𝗯𝗶𝘁𝗰𝗼𝗶𝗻 inside Square, with fee-free promos at launch. 𝗪𝗵𝗮𝘁 𝗜’𝗹𝗹 𝘄𝗮𝘁𝗰𝗵: accuracy in noisy environments, smart upsells (add sides/drinks without being pushy), and real-world impact on 𝗽𝗵𝗼𝗻𝗲-𝗮𝗻𝘀𝘄𝗲𝗿 𝗿𝗮𝘁𝗲, 𝗯𝗮𝘀𝗸𝗲𝘁 𝘀𝗶𝘇𝗲, 𝗮𝗻𝗱 𝗿𝗲𝗺𝗮𝗸𝗲 𝗰𝗼𝘀𝘁𝘀. If those move, voice AI becomes a no-brainer line item rather than a lab experiment. — Would you let an AI take your restaurant’s phone orders during peak hours? Why or why not? P.S. I’m continuing this theme on my Substack – deep dive here: https://lnkd.in/eG7TbJbJ #Square #Block #Restaurants #VoiceAI #POS #HospitalityTech #OrderAhead #Fintech #Bitcoin #QSR #CustomerExperience #Automation

Imagine never manually ordering food again. Neil Agarwal, co-founder of Refix Analytics, connected Swiggy to an AI assistant called Clawdbot and automated his daily food and grocery routine. Now: • Chai arrives at 5 PM automatically • Groceries get ordered based on planned meals • Dinner suggestions adapt to his mood The setup? One minute. After that, it runs on autopilot. Before placing an order, the AI: • Generates a full cost breakdown • Shows delivery charges & taxes • Warns if cancellation isn’t allowed • Asks for explicit confirmation Then places the order. Clawdbot isn’t a typical chatbot. It remembers routines, preferences, past interactions and works inside WhatsApp, Telegram, iMessage, and Discord. But quietly removing small, repetitive headaches from everyday life. Would you trust AI to auto-order your food?

Your B2B customers aren't at a desk. They're in trucks, on job sites, between meetings. They shouldn't fill out order forms. They should call. And they do call your sales rep. Voice still dominates B2B ordering. The problem? Your sales rep takes the order. Manually enters it. Takes 10 minutes. Costs you $15 in labor. Meanwhile, simple questions like "Where's my order?" "Can you change my shipping address?" burns rep time, while they should be focusing on creating complex quotas, advising top accounts, and closing new deals. Quick build-up tutorial based on recent client need: → Voice agent built at ElevenLabs handles intake → Draft order created in Medusa → Sales rep reviews, approves, and sends a quote  → AI agent handles support questions like a change of address Zero rep time until the quote goes out. If your reps are still taking orders by hand, you're paying $15 for a task that costs <$0.1

Swiggy just made typing optional. Speaking is the new scrolling. And India's next billion users are the reason why. On March 25, 2026, Swiggy announced a strategic partnership with Sarvam AI, an Indian sovereign AI company, to launch full voice-led commerce across its platform. Users can now order food, shop for groceries on Instamart, and book restaurant tables on Swiggy Dineout using simple voice commands across 11 Indian languages, including Hindi, Tamil, Telugu, Kannada, Bengali, and Marathi. Yahoo! Here is what makes this genuinely different: The entire journey, from product discovery to checkout and payment, is handled through conversation. No buttons. No menus. No typing. RT International Users can also place orders over a regular phone call, with no smartphone app or internet connection required, opening access to millions in low-connectivity and underserved regions. RT International Swiggy is also the first commerce platform to go live on Indus, Sarvam's AI-native chat application, with Razorpay powering the payment leg of the transaction. Middle East Eye Swiggy CTO Madhusudhan Rao said it best: "True accessibility means meeting users where they are, in the languages they speak." The business case here is enormous. India has 22 officially recognised languages. Over 900 million internet users, as per TRAI data. Yet most digital commerce still defaults to English. Swiggy's move aims to onboard millions of new users by shifting from screen-based interactions to voice-first experiences, redefining how consumers interact with digital services in India. UNITED24 Media This is not a feature update. This is a distribution strategy. Whoever wins the voice layer wins the next wave of Indian commerce. Are you building for the user who types, or the one who talks? Follow me for more breakdowns on India's tech and business ecosystem. #Swiggy #SarvamAI #VoiceCommerce #AIIndia #IndianStartups #Instamart #Dineout #ConversationalAI #DigitalIndia #LinkedInIndia #TechIndia #FutureOfCommerce

We just built something that didn't exist six months ago. An AI agent that calls your customer, recovers the abandoned cart, handles every objection, and collects the payment. On the same call. No human. No handoff. No delay. This is what we've been working on with Razorpay and I want to explain why this is a bigger deal than it sounds. Right now, every e-commerce brand in India has the same broken workflow. Customer abandons cart. Brand fires an email. Customer ignores it. Brand fires an SMS. Customer ignores it. Brand fires a retargeting ad and pays for the same customer twice. Meanwhile the actual reason they left, a question about delivery, a doubt about returns, a moment of hesitation that a single conversation could have resolved, never gets addressed. Because there was nobody there to have the conversation. That's the gap we've been obsessing over. Not the marketing funnel. Not the checkout page. The moment after intent is established and before the payment goes through. That window 20 minutes, maybe 30, where a customer is still warm, still interested, still recoverable. We built a voice AI agent that lives in that window. It calls within minutes. It knows exactly what was in the cart. It speaks the customer's language. It answers the question that caused the drop. And when the customer says yes, it generates a Razorpay payment link, sends it in real time, and confirms the transaction before the call ends. From abandoned cart to paid order. One conversation. Zero humans required. And it doesn't stop there. COD order placed? Agent calls immediately, confirms address, converts to prepaid with an incentive. Payment overdue? Agent follows up, sends the link, collects on the call. Post-purchase upsell? Agent calls after delivery, recommends the next product, closes the reorder. The entire commerce journey, conversation, decision, payment, confirmation handled by one agent, end to end. What this actually means for a D2C brand running at scale: Every abandoned cart gets a real conversation within 20 minutes. Every COD order gets confirmed before it ships. Every collection followup happens automatically. Every upsell opportunity gets acted on. Not when a human is available. Every time. Immediately. At any volume. We've spent months on this because we believed one thing, the future of commerce isn't a better checkout page. It's an agent that closes the sale the way your best salesperson would, by actually talking to the customer. superU AI + Razorpay is that agent. If you're running a D2C brand and recovery, conversion, or collections, this was built for you.