About the Client

The client is a leading U.S.-based semiconductor company specializing in high-performance computing solutions for industrial automation, automotive, and IoT markets. With global operations and a strong portfolio of microcontrollers, SoCs, and edge AI accelerators, the client is committed to delivering next-generation solutions with ultra-low latency and high data throughput.

The Client Challenge

The client was witnessing a significant shift in its customer base, demanding faster, real-time processing at the edge, especially for applications in autonomous vehicles and smart manufacturing. Their existing architecture was heavily cloud-dependent, leading to increased latency, high bandwidth costs, and limited offline capabilities.

The challenge was twofold: First, they needed to transition to a decentralized edge computing model without disrupting their existing infrastructure. Second, they required hardware-software co-optimization that could support low-power, high-throughput computation closer to the data source.

Security and device management at scale posed additional concerns, as the client was targeting deployments across thousands of industrial IoT devices. Furthermore, there was a pressing need to accelerate development cycles and reduce time-to-market for their edge-based platforms, while maintaining the flexibility to integrate AI/ML capabilities at the edge.

They were looking for a technology partner who could provide system-level expertise, end-to-end support across hardware and software, and agile delivery to align with their aggressive roadmap.

Spanidea Solution

Spanidea designed and delivered a comprehensive edge computing solution that spanned embedded platform development, system optimization, and AI inference acceleration. The engagement was executed through Spanidea’s agile engineering model and included the following components:

• Hybrid Delivery Model
  Spanidea deployed a blended team across its U.S. and India locations to accelerate development while optimizing costs. Senior architects in the U.S. collaborated directly with the client’s R&D team, while offshore teams handled platform bring-up, driver integration, and continuous validation.
• Custom Edge Platform Development
  Spanidea built a custom Linux-based edge platform using the client’s SoC and microcontroller portfolio. The system supported real-time OS extensions, edge AI libraries, and secure boot mechanisms. The platform included support for heterogeneous computing cores to optimize processing workloads.
• AI/ML Integration and Optimization
  Our AI team collaborated with the client to port and optimize AI inference models using TensorFlow Lite and ONNX on embedded targets. Leveraging NEON and DSP acceleration, Spanidea achieved a 3x improvement in inference time for vision models critical to their smart factory applications.
• Edge-Oriented Middleware Stack
  Spanidea developed a lightweight middleware stack that included real-time messaging, OTA (Over-the-Air) update frameworks, telemetry capture, and remote diagnostics. This middleware enabled seamless device management and secured data pipelines from edge to cloud.
• System Validation and Optimization
  We conducted thermal profiling, power optimization, and end-to-end latency benchmarking. Spanidea’s team implemented power gating and dynamic frequency scaling to achieve ultra-low power consumption under edge workloads.
• Security Architecture
  A security-first architecture was implemented, including secure boot, encrypted firmware updates, and runtime anomaly detection. These measures ensured the edge devices could be safely deployed in sensitive industrial and automotive environments.
• DevOps and CI/CD Pipeline for Edge
  Spanidea established a complete DevOps pipeline using Yocto-based builds, GitLab CI, and automated hardware-in-the-loop (HIL) testing. This enabled the client to perform nightly builds, detect regressions early, and deliver OTA updates confidently across their global device fleet.
• Consulting and Roadmap Planning
  Spanidea’s consultants worked closely with the client’s product leadership to define a future-ready roadmap for modular edge solutions that could support evolving industry standards and next-gen AI workloads.

Business Benefits

With Spanidea’s edge computing solution, the client achieved a 60% reduction in data processing latency, enabling real-time decision-making in factory automation and autonomous systems.

Bandwidth consumption was reduced by 45% by processing data locally, allowing for significant cost savings across thousands of deployed units. The custom middleware and OTA stack improved device manageability and uptime by over 30%.

AI workloads at the edge were optimized for performance and power, reducing model inference time by up to 70% on embedded targets. Additionally, the new DevOps-driven development cycle shortened time-to-market by 40%, enhancing the client’s competitive edge.

The platform is now being used as a baseline for future product lines, and Spanidea continues to support with long-term roadmap planning and dedicated engineering resources.

About Spanidea

Spanidea is a global technology services company delivering full-stack engineering solutions across embedded systems, IoT, AI/ML, and digital transformation. With deep expertise in semiconductors, networking, automotive, and edge computing, Spanidea empowers clients to build intelligent and scalable products. Our global delivery model, combined with innovation-driven teams, enables us to deliver complex solutions with agility, speed, and reliability.