Operational Edge AI in Embedded Systems

Edge AI empowered by aicas

Move Faster to Production

New AI models are being developed for Edge AI and Physical AI use cases at rapid speed. Making them perform well in edge operations with bandwidth, latency, and compute challenges everywhere is another story. Not to mention that AI models require the best data to be trustworthy.

aicas EdgeSuite - Turn Your AI Project into Reality Faster

aicas enables the reliable deployment of Edge AI within existing physical infrastructures, helping organizations gain market presence more quickly. The aicas EdgeSuite provides a unified AI DevOps platform for testing, deploying, and operating Edge AI in embedded systems.

It seamlessly integrates with leading AI tools from OpenAI, Anthropic, Amazon, and Meta through the MCP interface. The aicas AI Agent, integrated or complementary to the aicas EdgeSuite, provides the additional state-of-the art comfort and usability that users expect today.

4 Steps to Get Your AI Use Case Production Ready

1 Connect & Capture

Connect edge devices and fleets. Select device signals for high-quality operational data. EdgeSuite works seamlessly with MQTT, CoAP, PCUA, HTTP/REST, and other protocols.

2 Train & Test

Train and test Edge AI models with prioritized live data. Use the EdgeSuite as a pre-production sandbox.

3 Deploy & Run

Deploy AI models into heterogenous target edge infrastructures. Monitor and learn with realtime insights from system inference on device fleets using the integrated dashboard and feeds.

4 Improve & Update

Continuously monitor, train, and update AI models. Use aicas’ integrated software management tools or Docker-based platforms and more.

Step 1

1 Connect & Capture

Connect edge devices and fleets. Select device signals for high-quality operational data. EdgeSuite works seamlessly with MQTT, CoAP, PCUA, HTTP/REST, and other protocols.

Step 2

Train & Test

Train and test Edge AI models with prioritized live data. Use the EdgeSuite as a pre-production sandbox.

Step 3

Deploy & Run

Deploy AI models into heterogenous target edge infrastructures. Monitor and learn with realtime insights from system inference on device fleets using the integrated dashboard and feeds.

Step 4

Improve & Update

Continuously monitor, train, and update AI models. Use aicas’ integrated software management tools or Docker-based platforms and more.

Take a look at the automotive AI workflow with aicas EdgeSuite.

What’s in it for You

40+% faster time-to-solution with lean engineering
Improved model quality with better training data
Shorter AI model validation cycles
Faster time-to-market for customer AI pilots

Why Work With aicas

For 25 years, customers have relied on the uncompromised quality of aicas’ products in edge-to-cloud software solutions. Serving Fortune 500 companies, partners, and segment leaders in automotive, mobility, industrial, and A&D segments.

Close to 35 million devices in operation
Proven in safety-critical and realtime system
Partnerships with AWS, NXP, Qualcomm, BlackBerry QNX, and others

What You Get With aicas EdgeSuite

If you are thinking about prototyping your AI application

Easy device setup and management using web interface
Targeted data collection via filtering from signals
Automated deployment and testing in sandbox
User-friendly setup of simulation systems

If you are ready to run AI DevOps processes in production at scale

Full automation loop to run AI models on edge fleets
Full control over the software deployed, inlcuding debugging tools
Remote data management, data ontology available on- / off-air
Live inference and performance monitoring via dashboards and feeds

Explore the aicas EdgeSuite to Get Your AI Use Case Up and Running

Get Started with aicas EdgeSuite!

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