AI on the Edge Made Simple

A multi tenant platform that turns complex edge AI pipelines into a one click experience for data scientists and device engineers.

AI on the
Edge Made Simple

A multi tenant platform that turns complex edge AI pipelines into a one click experience for data scientists and device engineers.

Chapter 1 — The Introduction

A New Standard for Deploying AI Models at the Industrial Edge

NXP wanted a radically simpler way to bring AI to the edge. Instead of months of engineering work, they envisioned a platform where data scientists could collect data, train models and deploy them to devices with a single click. No firmware work, no infrastructure management, no device compatibility concerns. Together we created a multi tenant and fully serverless platform that makes edge AI accessible to every team inside NXP and, in the future, to partners and customers worldwide.

From raw sensor data to real time inference

The platform standardizes how data from sensors, machines and industrial equipment flows into AI pipelines. Any sensor can be connected to the NXP AI Box: vibration, temperature, audio, images, or even enhanced generative streams. Data becomes instantly available to data scientists, who can train models and deploy them back to edge devices with a single click. What took internal NXP teams two years to explore was delivered in just three weeks through Synadia’s serverless and rapid development approach.

Chapter 2 — The challenge

Standardizing edge data, simplifying AI deployment and accelerating innovation

NXP needed a unified way to standardize sensor data, deploy AI to devices easily and remove the complexity that typically slows down industrial edge development.

Standardizing diverse sensor data for AI use

Factories contain many different sensor types. They produce vibration signals, audio patterns, thermal readings, pressure curves, images and more. Each sensor speaks its own language, forcing data scientists to spend valuable time on formatting, cleaning and structuring data. The challenge was to design a unified pipeline that processes all data in a consistent and AI ready way, while still giving data scientists full flexibility to explore and experiment with it.

Removing technical barriers for deploying AI to devices

Traditional edge AI deployment requires deep firmware knowledge, device provisioning, protocol integration, cloud infrastructure and custom tooling. These responsibilities do not align with the role of a data scientist. NXP needed a system that automated everything: device security, provisioning, routing, model packaging, update flows and inference logic. The goal was to allow non technical users to deploy models to devices with complete simplicity.

Building a global platform in record time

The platform needed to support internal factories first and later external customers. It required multi tenancy, strict security, offline functionality, real time processing and support for many industrial protocols. Normally such systems take years to develop. Synadia, using a fully serverless design, delivered a working prototype in three weeks that exceeded expectations and replaced two years of exploratory development within NXP.

Chapter 3 — The project

An automated environment for collecting, training and deploying AI at the edge

Synadia delivered the complete AI edge platform with a secure and fully serverless architecture on AWS, designed for instant device onboarding, automated data flows and simple AI deployment.

A secure and standardized foundation for every device

We built the NXP AI Box and edge software as a unified and secure IoT foundation. Certificates are issued automatically, devices are provisioned without manual work and any sensor can be connected without firmware modification. Data is buffered locally and transmitted to the cloud platform when available. Whether a factory uses one sensor or one hundred, the configuration happens entirely in the cloud through the platform.

AI pipelines that automate the entire journey from sensor to inference

The platform processes raw sensor data and converts it into AI ready structures. Data scientists can access this data instantly and train models directly. When a model is ready, it can be deployed to devices in seconds. The platform supports updates, version control, rollback, real time monitoring, inference scheduling and error handling. Everything is configurable through a graphical interface instead of code.

A global multi tenant platform prepared for commercial rollout

The system supports many factories, partners or organizations within one shared global platform. Every tenant is isolated while still benefiting from one extremely efficient serverless backbone. Devices can connect from anywhere within minutes. Offline capabilities ensure continued operation without cloud access. Privacy settings allow users to keep data local while still taking advantage of AI capabilities.

Chapter 4 — The result

A scalable and production ready platform for real time AI at the industrial edge

The platform is now operational, connecting AI Boxes worldwide and enabling NXP to accelerate innovation, reduce complexity and bring edge AI to production environments.

AI deployment becomes a one click action for data scientists

Teams can now connect devices, collect data and deploy AI models instantly. There is no need for firmware engineers or cloud specialists. What once involved months of effort now takes seconds. Data scientists control the full workflow from experiment to deployment without depending on traditional engineering cycles.

A platform that supports factories worldwide

Factories and global teams receive their own isolated environment within the same platform. The entire lifecycle from data ingestion to inference execution is automated. Demonstrations at CES confirmed the robustness, speed and commercial readiness of the platform. The MVP is live and expanding rapidly as NXP scales the solution.

High performance, secure and fully operational even offline

The AI Box continues to run inference even when internet connectivity is unstable or unavailable. Updates arrive in seconds, and users can choose whether data syncs to the cloud or stays local. NXP now operates a secure and high performance edge environment that is simple to use and easy to scale.

Chapter 4 — The benefits

A future ready AI ecosystem that transforms NXP into an AI solutions provider

The platform accelerates innovation, reduces operational cost and enables powerful AI solutions across factories, partners and customers.

Key advantages realized through the NXP edge AI platform

  • AI deployment reduced from months of engineering to a single click

  • Standardized data pipelines that accelerate experimentation

  • Extremely low operation cost through serverless cloud architecture

  • Fully secure IoT onboarding with certificate based authentication

  • Real time insight and inference for every factory and sensor

  • Multi tenant foundation for global commercial rollout

  • Moves NXP from hardware supplier to AI solution provider