What types of automotive systems can Eggplant help modernize?

Eggplant tests and automates workflows across infotainment systems (IVI), ADAS, in-vehicle connectivity, digital cockpit displays, telematics platforms, and customer-facing mobile apps. The strongest fit is HMI testing (dashboard interactions, voice commands, touchscreen workflows) where image recognition handles the visual complexity that script-based tools cannot.

Can Eggplant test embedded automotive systems and legacy ECU software without disruption?

Yes, because Eggplant tests at the UI level using image and text recognition rather than code-level hooks, it validates embedded ECU software, legacy CAN-bus interfaces, and proprietary OEM platforms without requiring access to source code or vendor-restricted APIs. This is essential for tier-1 suppliers and OEMs working across mixed legacy-and-modern vehicle architectures.

What regulatory and compliance frameworks does Eggplant support?

Eggplant generates evidence aligned with ISO 26262 functional safety (ASIL A through D), ISO/PAS 8800 AI safety, UN R155 cybersecurity, UN R156 software update management, and ISO/SAE 21434 automotive cybersecurity. Test execution captures the traceability, evidence, and reporting that automotive auditors and Type Approval authorities expect.

Can Eggplant scale for global automotive enterprises and connected vehicle ecosystems?

Yes. Eggplant is used by global OEMs including NIO, which reduced manual testing effort by approximately 40% across its R&D function. It supports distributed test execution across regions and engineering centres, role-based access for separated teams, and integration with enterprise CI/CD toolchains.

How does Eggplant integrate with automotive DevOps practices and engineering environments?

Eggplant integrates with Jenkins, GitLab, Azure DevOps, and automotive-specific toolchains. For requirements traceability, it connects with DOORS, Polarion, and Jama, which is essential for ISO 26262 compliance where every test must trace back to a safety requirement.

How quickly will I see results after implementing Eggplant?

Most OEMs see meaningful results within the first quarter. NIO digitised its testing processes and freed engineering time previously consuming roughly 40% of tester capacity. Initial wins typically come from automating high-frequency regression workflows (infotainment displays, dashboard alerts, ADAS configuration variants) where the manual effort is highest.

Automated Software Testing for Automotive

Eggplant for automotive HMI test automation, infotainment validation, and ADAS software testing. ISO 26262 evidence generation across embedded, connected, and AI-enabled vehicle systems.

Your Scripts Test the Interface. Not What the Driver Experiences.

Modern vehicles run more software than most enterprises. Infotainment, ADAS, telematics, OTA update managers, digital cockpit displays, each with its own release cadence, vendor, and compliance obligation. Script-based automation breaks on every HMI update. Manual testing can't scale across the variants. And a defect in ADAS or a safety-critical alert isn't a bug, it's a recall.

Why Automated Software Testing Matters in Automotive

Comprehensive In-Vehicle Coverage

Test every part of your automotive software environment – from infotainment and ADAS to connected car platforms. Even the most complex interactions, like voice commands, navigation, and safety critical functions, can be fully automated and validated.

True End-to-End Workflow Testing

Run a single test that spans the entire automotive ecosystem. Validate in-vehicle software, confirm connectivity with backend systems, and ensure updates flow across infotainment, telematics, and mobile apps, all in one seamless workflow.

Automated Safety and Compliance Assurance

Stay ahead of failures with continuous, automated testing. Eggplant helps you meet ISO 26262 and other regulatory requirements, validates security updates, and reduces costly recalls, keeping vehicles safe, compliant, and road-ready.

Driver-Centric Experience Validation

See your systems the way drivers and passengers do. Eggplant validates screens, alerts, and digital controls with advanced image and text recognition, ensuring every display, dashboard, and interface looks and works exactly as intended.

What You Get

AI-driven software testing for every critical automotive system and workflow.

Reduce Cost & Complexity

AI-driven, reusable models reduce testing costs and complexity, automates compliance and regression testing, and ensures consistent driver experiences by validating dashboards, alerts, and HMI displays.
Ensure Safety

Our AI-driven automation tests HMI systems the way a real driver would– pressing buttons, reading displays, and validating every response. You'll speed up testing cycles, cut down on errors, and deliver safer, more reliable automotive software faster.
Release Quicker

Automate the toughest aspects of HMI testing, validating every configuration, testing infotainment, ADAS, and connected systems in real-world conditions, and ensuring compliance with legal and safety requirements, while accelerating releases and staying audit-ready.
Accelerate Delivery & Scale

Seamless integration with CI/CD pipelines accelerates delivery and scales continuous testing across embedded and cloud systems – helping you release faster without compromising safety.

See It in Action

Validate the Whole Drive, Not Just the Dashboard

See how testers automate EV, IVI, and in-vehicle network validation, driving Vector CANoe simulations end to end. Real CarPlay journeys across devices, networks, and CAN bus, with coverage up and manual effort down.

Watch Test Talk

Real Automotive Use Cases

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AI Validation and Integrity

In automotive, software reliability is safety-critical, and so is being able to prove it. Keysight covers both sides: testing that your software works, and validating that your AI can be trusted.

Testing software is one challenge. Proving that the AI inside your vehicle is trustworthy is another. International standards and regulators are calling for more than just accuracy metrics. They want to understand how AI makes decisions and require proof of AI safety – "it usually gets it right" isn't an answer.

The AX1000A AI Software Integrity Builder addresses this by validating AI across the full lifecycle: from dataset quality checks and model behavior to real-world inference testing, generating evidence aligned with emerging standards such as ISO/PAS 8800.

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