How Invenda Bridges Manufacturing & Digital with IoT

About Invenda

Invenda Group AG is a Swiss company that builds IoT-enabled vending machines and a unified software platform for next-generation smart digital out-of-home (DOOH). The platform connects physical devices with cloud services, digital payments, and advertising analytics. Founded in 2017, the company has deployed over 9,000 screens for clients including Mars Wrigley and Coca-Cola. As Invenda scaled, IoT software development became the core of its growth strategy: the platform, branded Luna, manages everything from remote pricing and real-time inventory tracking to programmatic ad delivery and predictive maintenance.

Invenda is not a traditional hardware manufacturer. The physical machines are one layer of a broader digital ecosystem. What makes the company distinct is that every machine doubles as a media endpoint: the 49-inch touchscreens serve as both retail interfaces and programmable advertising displays. It is a model few competitors have matched, and it has positioned Invenda as a leader in connected retail.

The Challenge: Scaling a Connected Retail Platform Across 22 Countries

As Invenda's fleet expanded across regions, managing it called for a more granular approach than the original system was designed for. Configuring machines by location, assigning operator permissions across organizational levels, and adjusting pricing by market all needed to work at a scale the company had not operated at before.

At the same time, the platform was generating massive volumes of data (transactions, ad impressions, sensor readings) without an infrastructure to process it. The advertising system alone produced tens of millions of metadata records every few months, with no efficient way to surface reporting for operators and advertisers.

As Invenda expanded into new markets and onboarded larger clients, a formal security assessment of its consumer-facing APIs became a priority to ensure the platform met industry standards for protecting wallet balances, purchase history and loyalty data.

All these constraints were growing in parallel. The faster Invenda expanded, the more visible each need became.

How Accedia’s Team Embedded Across Workstreams

Accedia joined at a key moment in Invenda's growth, when the company needed additional engineering capacity to keep pace with expanding markets and a growing client base. Led by an Engineering Manager, Accedia's developers work alongside Invenda's architects and product leads across several connected areas: on-machine payments, cloud fleet management, digital advertising infrastructure and security.

On-machine payment and transaction processing

Every vending machine in Invenda's fleet can run a different combination of payment terminals, sensors and motor assemblies. Logic that works with one configuration may behave differently with another. Together with Invenda's engineering team, Accedia develops and extends the backend that accounts for these variations across the entire fleet: the transaction pipeline from basket to payment authorization to product dispensing. A separate hardware communication service manages interaction with physical components via the Multi-Drop Bus (MDB) protocol, handling motor retries when products fail to dispense, payment terminal responses and sensor monitoring.

Key features include partial refund logic (automatic refund when a machine fails to deliver one of several purchased items), remote power cycling from the cloud admin panel through Azure IoT Hub and multi-price support that lets operators set lower prices for card payments versus cash (reflecting the higher operational cost of cash handling). MongoDB replicates data between the machine and the cloud bidirectionally: when connectivity drops, transactions queue locally and sync automatically once the connection returns.

Fleet management and digital advertising at scale

Luna 2.0 introduces a hierarchical organization structure that lets operators manage thousands of machines by region, sub-region, and location. Accedia helps develop the platform, with role-based access control ensuring the right permissions at every level.

On the advertising side, the team develops the Atlas infrastructure, working on the integrations that connect Invenda's vending screens to third-party ad platforms. The screens handle three modes (active purchase, passive ad display and out-of-service restocking) and report delivery data back to operators and advertisers. The network now serves over 1 million ad plays every month.

Data analytics and reporting infrastructure

The machines generate transaction records, sensor readings, audience impressions and ad performance metrics continuously across the fleet, but raw volume without structure is noise. The data pipelines run on Azure Databricks, where Accedia contributes to the ingestion, processing and reporting layer, with machine learning workloads supporting predictive maintenance and user behavior analysis. The same infrastructure supports operational analytics: machine performance, locations that need attention and how buying behavior varies by region. All data processing is designed to meet GDPR requirements across Invenda's European markets.

Security assessment of payment and fleet APIs

Accedia's cybersecurity team assessed the Luna CMS API and the Wallet API (Tapp) against OWASP Top 10 and OWASP IoT Top 10 vulnerabilities. Testing covered REST API endpoints, the Angular web interface, and MDB hardware communication protocols using Burp Suite Professional, Kali Linux, and directory enumeration tools. All identified gaps were addressed, and every industry-standard security measure has been implemented. For a company processing consumer payments and managing loyalty data across multiple markets, this assessment strengthens Invenda's position as a trusted partner to operators and the global brands that rely on its network.

Technology Stack

• On-machine backend: .NET/C#, MongoDB, gRPC, SignalR for transaction processing, hardware communication and real-time machine-to-cloud sync
• Cloud and data: Azure IoT Hub, Azure Databricks, Azure Functions, PostgreSQL, Python for fleet configuration, data pipelines, ML workloads and serverless event processing
• Frontend: Angular for operator admin panels and web interfaces
• DevOps and CI/CD: Azure DevOps, Azure Pipelines, GitHub for version control, continuous integration and deployment automation
• Cybersecurity: Burp Suite Professional, Kali Linux, gobuster for penetration testing and vulnerability assessment
• Protocols: MDB (Multi-Drop Bus) for low-level communication between vending machine components
• Security standards: OWASP Top 10, OWASP IoT Top 10

Where the Platform Is Heading

Hyper-personalized Advertising

Invenda’s next phase centers on hyper-personalized advertising. The vision is for each machine to tailor what it shows based on who is standing in front of it, the time of day, weather conditions, and purchasing patterns at that specific location. A customer approaching a machine on a hot afternoon would see different product recommendations and pricing than someone at the same spot on a cold morning. The groundwork is already underway: the current focus is on collecting audience impressions and behavioral data across the fleet, building the dataset that future personalization will rely on. The roadmap also includes camera-based age verification for restricted products and dynamic pricing that adjusts automatically based on contextual factors.

AI-assisted development and faster release cycles

Accedia and Invenda are bringing AI into the development process through GitHub Copilot, an AI-powered coding assistant that can help developers write code faster, catch errors earlier, and reduce time spent on repetitive tasks. To support broader adoption, the teams plan to consolidate their codebase and CI/CD pipelines by migrating from Azure DevOps to GitHub. They are also introducing feature flags so new functionality reaches production faster while remaining hidden from end users until it is ready to go live.

Business Impact: How the Collaboration Accelerated Invenda's Growth

What began as a capacity constraint has become an expanding technical partnership. Since the collaboration began, Invenda's business has continued to scale. The company reports that operators using its IoT ecosystem see up to 30% higher revenue per machine. The patterns behind Invenda's evolution extend well beyond connected retail. Fleet management, real-time telemetry and IoT security are challenges that any organization building manufacturing IoT solutions will recognize.

Invenda's ambition is to become a software-first company, where the technology is the product and the machines are one way to deliver it. That focus is what has put the company at the front of its industry, and Accedia's engineers are helping build what comes next.