Software. Data. Edge AI.

aicas EdgeSuite

Unify software, data, and AI management across distributed edge environments. Built for the edge. Ready for AI.

Software Management

Deploy, update and manage edge software and AI across edge devices

Data Management

Capture and select operational data from real-world edge systems.

AI Management

Deploy & improve AI models for inferencing at the edge through continuous cloud-to-edge cycles


aicas EdgeSuite

One Platform for Software, Data, and AI at the Edge

aicas EdgeSuite is a scalable edge-to-cloud platform for deploying, managing, and improving software over its lifetime. It covers life-cycle management, data workflows, and AI-enabled applications across distributed edge environments.

It enables technical teams to deploy new capabilities, leverage operational data, and optimize intelligent systems while in production.

Backed by more than 25 years of embedded software expertise, aicas technology has been deployed to nearly 35 million connected devices worldwide from mobility and automotive, industrial and energy, to medical and aerospace and defense sectors. 

Built for the edge. Ready for AI.

35

Million

connected devices

25

Years

edge experience

Proven

in
mission-critical
systems

Trusted

by global
industry leaders


The Challenge

Manage Growing Edge Complexity

As device fleets grow and system variants multiply, managing distributed edge environments becomes increasingly complex. Software, data, and AI must be deployed and operated reliably across different devices, hardware platforms, and infrastructures, where limited compute resources and connectivity are common.

Tools and workflows make this even harder. They increase integration effort, slow down deployments and updates, and make it difficult to turn large amounts of edge data into useful insights. Organizations need a more unified way to manage software, data, and AI at scale and continuously improve intelligent systems in the field.


Lifecycle Management

Connect Development and Operations in a Continuous Loop

Observe. Build. Deploy. Operate. Improve.

Successfully operating Edge AI requires more than deploying models. Software, operational data, and AI-enabled applications must continuously evolve based on insights from real-world systems. EdgeSuite connects operational environments with software, data, and AI lifecycles, creating a continuous feedback loop across distributed edge systems.

Observe

Collect relevant operational and inference data from vehicles, machines, infrastructure, and other connected assets

Build

Design, develop, train, and test software and AI models using operational insights from real-world environments.

Deploy

Distribute software updates, configurations and AI models securely across distributed fleets.

Operate

Run software and AI-enabled applications reliably in production environments and monitor their performance.

Improve

Use operational feedback to improve software, data workflows, and AI performance over time.


Operational Outcomes

Streamline Embedded System Development

By connecting software, data, and AI lifecycles across cloud and edge, EdgeSuite helps technical teams reduce fragmentation and operate distributed systems more efficiently.

Reduce Operational Complexity

Use a single platform to keep better control over software, data and AI model management.

Scale Across Distributed Systems

Deploy software, configurations, and AI-enabled applications across distributed heterogeneous device fleets.

Reduce Data and Cloud Costs

Select relevant data at the edge and filter out up to 90% of irrelevant data before transmission.

Drive Better Decisions

Use selected real-world data to understand system behavior and analytics to support informed decisions.

Enable Continuous Improvement

Connect operational feedback with software, data, and AI lifecycles to improve systems over time.

Support Mission-Critical Reliability

Combine memory-safe execution with realtime capabilities for demanding, mission-critical environments.


Showcase

AI powered Battery-Management-System

AI-enhanced Battery Management Systems can use real-world vehicle and battery data to improve the utilization of EV batteries and better predict SoX parameters. The operational challenge begins when these models move from development into production and need to be maintained across vehicle fleets.

Manage the AI Lifecycle Across Connected Vehicle Fleets

Together, NXP eIQ® Auto and aicas EdgeSuite connect AI development with real-world operation. NXP eIQ® Auto supports the development and optimization of AI workloads for NXP automotive platforms and hardware, while EdgeSuite provides MLOps infrastructure across the fleet.

EdgeSuite supports controlled deployment, in-field monitoring, and selective collection of inference and trainings data for subsequent development cycles. Updated models can then move through testing and validation before redeployment, creating a continuous and automated lifecycle.

Development → Deployment → Monitoring → Data collection → Improvement → Redeployment


Technical Foundation

Built for Real-World Edge Systems

Memory-Safe Execution
Run critical applications with greater protection against memory-related failures.

Realtime Reliability
Execute time-critical workloads with predictable, deterministic performance.

Device and Platform Independence 
Deploy across different hardware and operating environments.

Edge systems often operate under demanding timing, reliability, connectivity, and resource constraints. Built for mission-critical applications and challenging real-world environments, EdgeSuite combines memory-safe execution with real-time capabilities, enabling technical teams to operate reliable, high-performance systems at scale.

Reviewed and Approved by AWS
aicas EdgeSuite has been evaluated and approved by AWS and is qualified software to run on AWS cloud services.


EdgeSuite Products

Edge-to-Cloud. One Integrated Platform.

Cloud Layer

Edge Device Portal (EDP) →

Cloud-based portal for managing the lifecycle of software and AI components across distributed embedded and edge devices.

Edge Data Gateway (EDG) →

Cloud-based portal for accessing, precomputing, selecting, distributing, and visualizing data from embedded and edge devices. 

Edge Layer

JamaicaCAR →

Vehicle-specific functions and capabilities for the Automotive Domain as libraries and extensions to JamaicaVM and JamaicaAMS

JamaicaIOT →

IoT-specific functions and capabilities for IoT and edge-to-cloud applications across domains as libraries extensions to JamaicaVM and JamaicaAMS.

JamaicaVM →

Realtime Java Virtual Machine for developing and running memory-safe applications in embedded and mission-critical systems

JamaicaAMS →

Application Management System for managing the lifecycle, security, and resources of modular applications and services with realtime capabilities.


Next Step

Make Software, Data, and AI Work Seamlessly at the Edge

See how aicas EdgeSuite can help you to better deploy, manage, and run operations at the edge across distributed edge environments.

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