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How Tiago Godoi Is Building the Next Generation of Vending Machines

U-Get aims to turn vending into open-access shopping with facial authentication and automatic payment. Here’s how the system is described, what remains unknown, and what operators should weigh.
From TheFinanceBase Team8 min to read

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Tiago Godoi’s U-Get is trying to make vending feel less like a transaction at a machine and more like shopping from a self-checkout refrigerator: enroll in an app, open a participating unit with facial recognition, take an item, and leave to be charged. The important innovation is not just a camera on a vending machine. It is the combination of identity and access control, product recognition, and account-based settlement—an approach that may reduce checkout friction but brings new questions about privacy, accuracy, regulation, and cost.

What problem is U-Get trying to solve?

Traditional vending is convenient only when its constraints cooperate. Cash can be rejected, card readers can fail, products can jam, and customers may have to make a choice through a small window rather than browse naturally. Operators, meanwhile, must restock machines and monitor inventory, often without the visibility of a staffed store. Buying several items can add friction, and selling age-restricted products creates identity and compliance requirements.

A cashless, open-access cabinet can address some of those problems: a customer can browse, take products, and avoid paying at a physical terminal. But removing a card reader does not remove risk. Account credentials, payment processing, biometric information, recognition errors, and network outages all become part of the system’s risk profile. Convenience is not proof of better security.

Who is Tiago Godoi, and what is U-Get?

TechTimes’ August 7, 2024 profile describes Godoi as the founder of Brazilian smart-vending company U-Get. The profile says he started a software-development company at 16, studied Business Administration at the University of São Paulo, earned an MBA from the University of Michigan’s Ross School of Business, and worked at McKinsey, Meta, and Mercado Pago. It also associates him with Balizapp, SportsToGo, and Saxperto. These biographical details are reported in that profile, rather than independently established here. Read the TechTimes profile.

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U-Get’s LinkedIn company description presents the business as a smart-vending platform combining facial recognition, identity validation, machine learning, neural-network image processing, and robotics for access control. It says the company was founded in 2017 and is headquartered in São Paulo; its listed employee range is 2–10. Those are company-profile details, not audited operating facts. The company describes its equipment as adaptable to existing machines, but does not publish a compatibility list or enough detail to establish that it offers a standardized retrofit kit. See U-Get’s company description.

How the customer journey works

1. Enroll through the app

TechTimes reports that a customer downloads an app and registers facial data using a phone. The Smart2Get Google Play listing describes the app as a way to access smart refrigerators and says a user can register and use them without physical cash or a card. The listing is a snapshot of app-store information, not a full technical description of U-Get’s backend. View the Smart2Get app listing.

2. Authenticate and unlock

At a participating unit, the customer presents their face to the machine’s camera. U-Get identifies facial recognition as part of the access experience, but public materials do not explain whether it matches a face to a particular registered account, uses a different verification flow, or offers a non-biometric alternative. They also do not disclose liveness checks, performance under poor lighting or with facial changes, or how false rejections and false matches are handled.

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3. Take products and reconcile the purchase

Once recognized, a customer can take a drink or snack and leave, according to the TechTimes account. U-Get’s description names computer vision, image processing, neural networks, and robotics, which indicates a more involved system than a conventional vending payment terminal. The public description does not specify its sensors, camera arrangement, product-recognition accuracy, or how it resolves a product that is returned to the wrong shelf or not recognized.

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4. Settle the transaction

The reported model charges the customer’s account after the purchase. Public materials do not identify the payment processor or say whether the system preauthorizes an amount before unlocking. They also do not spell out receipts, refunds, disputes, failed payments, or reversals when a product is misidentified. Those details matter to consumers and operators because the machine’s convenience depends on accurate reconciliation as much as on fast access.

Why use facial recognition—and what are the alternatives?

Face-based access can spare a customer from pulling out a phone, card, or wallet, and tying access to an account may help a venue control who can enter a cabinet. That can be more useful for restricted products than for an ordinary snack machine. It also makes facial data part of the transaction, however, and the available U-Get materials do not establish how such data is stored, protected, retained, or deleted.

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The Smart2Get Play listing’s developer-provided data-safety disclosures say the app may collect personal and financial information, that data is not encrypted, and that users cannot delete it. App-store disclosures can change and may not describe the complete backend, so they should not be treated as a full security audit. They are nevertheless a concrete reason for users and prospective venue partners to ask U-Get how biometric and payment data are handled, what alternatives exist, and how account deletion works. Check the listing’s current data-safety disclosures.

Facial access is only one way to make unattended retail work. QR codes can avoid biometric enrollment but require a phone; tap-to-pay is familiar but still relies on payment hardware; PINs and app authentication are replaceable but add steps. ID scanning may support age checks, while creating its own document-data obligations. Other smart-fridge designs can use cameras and weight sensors to track items without making face recognition the defining feature. Which approach makes sense depends on the goods, venue, customer base, compliance burden, and total operating cost.

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What is known—and unknown—about U-Get’s technology?

U-Get publicly names facial recognition, identity validation, machine learning, image processing, neural networks, and robotics. In a deployed unit, a smart lock and refrigeration would also be practical components, while cameras or other sensors may support access and inventory functions. But the company has not published a complete architecture. The sources do not establish the camera count, whether processing happens on the device or in the cloud, model accuracy, training data, or how the system behaves when recognition or connectivity fails. It would be speculation to treat any particular sensor setup or algorithm as confirmed.

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That distinction matters: the system may need to answer several separate questions—who is allowed to open the cabinet, what products were removed, whether the shopper is old enough to buy a restricted item, and which account should be charged. Public descriptions do not show exactly which U-Get component answers each question. A camera-based identity check is not, by itself, proof of age, product recognition, or successful payment.

Where could this model fit?

U-Get specifically describes its platform for controlled consumer goods including alcohol, tobacco, and medicine. Identity and access controls could be commercially valuable in such settings, but that product positioning is not evidence of legal approval. Rules vary by jurisdiction and product: age thresholds, licensing, prescription requirements, permitted locations, recordkeeping, and responsible-sale obligations may all apply. A technically successful identity check does not make a sale lawful.

Potential venues and customers include offices, campuses, hospitals, transit hubs, retailers, beverage companies, and vending operators. The business case will differ by location. A high-traffic site with repeated purchases may benefit from faster browsing, while a low-volume site may not recover the added hardware, service, and compliance costs. A conventional cashless machine may provide enough convenience without biometric enrollment.

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What does the public evidence say about commercial traction?

TechTimes reported more than 400 deployed units and more than 30,000 recurring customers, as well as an international exclusivity agreement with an unnamed major soft-drink provider. These are company-profile claims reported by the publication; the available material does not independently verify them. The article does not identify the partner or disclose the agreement’s duration or scope. The reported figures and deal appear in the August 2024 profile.

Those figures alone cannot show whether the business is profitable or whether the units are still active. Public materials cited here do not disclose revenue, transaction volume, average order value, hardware cost, payment fees, maintenance costs, churn, geographic distribution, or payback period. The Smart2Get app listing snapshot also displayed 100+ downloads and an update date of October 18, 2023; app-store download counts are not a measure of total customers or machine usage.

How U-Get compares with other unattended-retail approaches

Approach What it emphasizes Trade-off or limitation
U-Get Facial access, identity validation, computer vision, and robotics, according to the company’s description. Public pricing, detailed system specifications, privacy architecture, and independent performance data are not stated in the cited sources.
Managed smart-fridge placement SmartMart describes a managed refrigerated-storefront service and says host locations pay zero cost for placement, with revenue from product sales. SmartMart The no-cost placement is a vendor claim, not a guaranteed financial outcome; it is a different model from buying and operating equipment.
Direct machine purchase XMAI lists Core 425 at $2,999, Pro 520 at $3,499, Max 680 at $4,499, and Ultra 1100 at $6,499 on its product page at the time represented by the supplied information. XMAI products Those listed hardware prices do not establish shipping, installation, software, payment, refrigeration, maintenance, or compliance costs.
Retrofit system Vendekin USA promotes a touchscreen retrofit for legacy machines, remote updates, error logs, and QR/mobile-wallet payments. Vendekin products The page directs buyers to request a demo or contact the company; public pricing is not stated.
Age-verification vending SMRT Vend markets age verification, ID scanning, app support, inventory management, and optional refrigeration. SMRT Vend The site offers custom quotes and says deployment can take as little as 30 days; public pricing and jurisdiction-specific approvals are not stated.
Camera-and-weight grab-and-go VMFS USA describes overhead cameras combined with weight-sensor verification and cloud monitoring. VMFS USA machines Configurations shown in search results ranged from approximately $3,950–$4,950; the exact configuration, shipping, and software terms require confirmation with the vendor.

The commercial choice is not simply which machine uses the most AI. Operators must decide whether biometric access is necessary, whether to own equipment or use a managed service, whether a retrofit is practical, what product categories trigger regulation, and whether the expected convenience justifies total operating cost.

What should consumers and operators check?

For consumers

  • Find out whether facial enrollment is mandatory and whether QR, app, or other access is available.
  • Ask how to view an itemized receipt, challenge a charge, request a refund, and close an account.
  • Review the current app data-safety disclosures and ask how biometric data is stored, retained, protected, and deleted.
  • Consider accessibility and what happens if recognition fails or a customer cannot use face-based access.

For operators and venues

  • Request total costs for equipment, retrofit, installation, software, payment processing, support, and maintenance—not just a machine price.
  • Ask for measured recognition and product-reconciliation performance in realistic lighting, connectivity, and multi-customer conditions.
  • Clarify downtime procedures, remote diagnostics, inventory integration, shrinkage responsibility, and refrigeration failure response.
  • Confirm camera placement, customer notice and consent, insurance, revenue share, restocking responsibility, and applicable product-sale rules.
  • Compare the business case with ordinary cashless vending or non-biometric smart cabinets before accepting added complexity.

What will determine whether Godoi’s approach scales?

U-Get’s concept addresses a real operational goal: make unattended shopping faster while controlling access and reconciling products. Its combination of biometrics, computer vision, and payment could be useful in venues where identity verification matters. Whether it represents a viable next generation of vending depends on evidence that is not established by the public claims alone: reliable performance outside ideal conditions, transparent data governance, workable regulatory compliance, maintainable equipment, and unit economics that beat simpler alternatives.

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Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.

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