In today’s industrial landscape, companies across manufacturing, transportation, logistics, and smart cities are rapidly adopting AI at the edge to enable real-time decision-making, automation, and predictive insights. However, while many organizations can successfully demonstrate AI proof-of-concept (PoC) using developer kits or off-the-shelf hardware, a growing number of customers are now facing a more difficult question:
How do we turn our AI PoC into a reliable, long-term production system that can survive in real-world industrial environments?
At the production stage, customers encounter a different set of challenges from wide temperature fluctuations, vibration, and 24/7 uptime requirements, to integration with multiple sensors, cameras, legacy systems, and strict industrial certifications. In many cases, the AI model may be ready, but the hardware platform is not.
This is where Premio’s expertise plays a key role. We design and engineer industrial-grade AI computing platforms that are tested, validated, and built to operate reliably in harsh field conditions for years. In this article, we’ll share how our hardware development process helps customers confidently scale their edge AI deployments from PoC to full production and why rugged edge AI requires far more than just computing power.
Why PoC Success Doesn’t Guarantee Production Success
Many organizations successfully complete their AI proof-of-concept using commercial developer kits, consumer-grade computers, or even general-purpose servers. These PoC systems are often deployed in controlled environments, lab settings, test areas, or short-term field trials where the primary focus is validating AI model performance, sensor integration, or software functionality.
However, moving from PoC to full production deployment reveals a new set of challenges that are often underestimated:
Environmental Extremes
Industrial environments expose hardware to wide temperature swings, humidity, dust, moisture, and other harsh conditions. Outdoor deployments, vehicles, and factory floors require hardware that can maintain stable operation under constant environmental stress.
Vibration & Shock
In transportation, robotics, and mobile AI, continuous vibration and occasional shock quickly cause failure in systems not built for rugged use. Loose connectors and fragile components often survive PoC but fail during extended field operation.
24/7 Continuous Operation
Unlike PoC trials, production systems must run non-stop. Hardware failures in 24/7 operations can lead to costly downtime, safety risks, and major disruptions to business operations.
Complex Sensor & Peripheral Integration
Edge AI deployments often involve multiple data sources such as GMSL cameras, PoE cameras, serial control, CANBus, and digital I/O. Many PoC systems lack the I/O flexibility and expansion options to handle these complex integrations.
Compliance and Certification
Production deployments must meet industry-specific regulatory and safety certifications (CE, FCC, UL, EN50155, IEC 62443, and others). Achieving these certifications requires careful hardware design, component selection, and extensive validation that most PoC hardware platforms are not built to support.
Long-Term Availability & Lifecycle Support
Industrial deployments typically run for 5–7 years or longer. PoC hardware often uses short-lifecycle components that face early end-of-life issues, creating supply chain risks for long-term projects.
Premio’s Development Process: From PoC to Production
As we’ve seen, moving from PoC to production introduces a set of hardware challenges that go far beyond basic AI performance. At Premio our development process is built to address these exact challenges, ensuring that every edge AI system we deliver is fully prepared for long-term, real-world deployment.
Here’s how we turn PoC concepts into reliable industrial-grade AI computing platforms:
System Architecture Built for the Real World
Every project begins with a careful system-level design. Before any hardware is built, we work closely with customers to fully understand the target application. Based on the demanding, we select the right platform architecture such as:
- Jetson Orin-based solutions for robotics, AMRs, railway vision, and transportation AI.
- Intel Core + PCIe GPU platforms for factories, surveillance, and smart city inference.
By aligning the hardware design with real deployment needs from the start, we avoid many of the integration problems that often appear when scaling PoC systems.
Ruggedization and Thermal Engineering
Unlike consumer or lab AI systems, industrial deployments must endure constant environmental stress. Our edge AI computers are built for fanless aoperation, using passive thermal designs to maintain stable temperatures without moving parts that attract dust or fail. They support wide temperature ranges of -20°C up to 70°C, with thermal simulations ensuring stability under full AI workloads. Mechanical robustness is a key internal component that is secured to withstand heavy shock and vibration, ideal for transportation, rail, and mobile robotics.
Testing and Validation for Harsh Conditions
To guarantee long-term field reliability, every design is put through extensive pre-production validation. This includes:
- Shock and vibration testing to simulate long-term operation in vehicles and mobile platforms.
- EMI/EMC testing to ensure electromagnetic compatibility with surrounding equipment.
- Ingress protection design for dust, moisture, and outdoor exposure.
Compliance and Industry Certifications
Many production deployments require official certification for safety, reliability, and regulatory compliance. Premio incorporates certification planning into the development process from the beginning. Our systems are tested and certified to meet:
- CE, FCC, and UL for general safety and EMC compliance.
- EN50155 and EN45545 for railway deployments.
- IEC 62443-4-1 cybersecurity standards for secure industrial system development.
This proactive approach shortens deployment timelines and reduces certification risks for our customers.
Long-Term Component Stability
In production, long-term availability matters just as much as performance. Many PoC systems fail when key components go end-of-life during deployment. To avoid this, Premio uses industrial-grade components with extended manufacturer support and tightly controlled BOM management, ensuring stable supply and easier future maintenance for customers managing large-scale deployments over multiple years.
Quality Control and Mass Production Readiness
Finally, every system entering mass production undergoes strict manufacturing quality control. Each unit is subjected to:
- Full burn-in testing under load.
- Production-level thermal and vibration testing.
- Consistent quality checks across every batch.
This ensures that every unit shipped performs reliably from day one whether it’s the first batch or years into production.
What Customers Gain by Building It Right from the Start
When edge AI systems are designed with deployment in mind from day one, customers avoid the most common pitfalls that slow down industrial AI projects. A production-ready platform reduces field failures, eliminates the need for redesigns, and accelerates time-to-market. It enables smoother integration with sensors and infrastructure, ensures compliance from the start, and lowers maintenance costs over time.
Most importantly, it gives customers the confidence that their solution will not only perform in controlled tests but also scale reliably in the real world.
Final Takeaways
Building an AI proof-of-concept is a great first step — but it’s only the beginning. When it comes to real-world deployment, the hardware must go beyond computing performance. It needs to be rugged, scalable, and reliable enough to operate 24/7 in harsh industrial environments.
At Premio we understand the challenges customers face when transitioning from PoC to production. That’s why we’ve built a development process that addresses every critical factor from thermal and mechanical design, modular I/O integration, and long-term component availability, to industry certifications and remote manageability.
We don’t just build edge AI systems that work, we build systems that last.
If you're looking to scale your edge AI deployment with confidence, talk to us. We're ready to help you move from concept to real-world success.