In Brief:
- Acsia’s evolution from Kanzi to Android Automotive shows how cockpit software is moving from standalone tools to connected ecosystems.
- By embedding its AI platform LiLA and introducing touch automation, Acsia has accelerated and refined HMI validation.
- With Kanzi One and a hybrid Kanzi–Android approach, it delivers cockpit experiences that combine creativity, safety, and performance for the SDV era.
In the early days of Acsia’s cockpit programs, Kanzi was the constant. It was the tool we trusted to deliver crisp visuals, real-time performance, and stability in safety-critical domains like instrument clusters and HUDs. Over time, we built deep expertise around it – not just in the technology itself, but in the discipline, it demanded: attention to every frame, every millisecond, every safety margin.
Our journey with Kanzi also marked a turning point in our growth. After proving ourselves with performance challenges like FastBoot clusters, we recognised that speed alone was not enough. To truly deliver cockpit experiences that inspire trust, we needed world-class HMI expertise. That led us to Rightware in Finland, where we became the first Indian team to undergo advanced Kanzi training. That experience not only deepened our technical mastery but also gave us a unique perspective on how to blend high-fidelity graphics with automotive-grade stability – lessons that continue to guide our cockpit programs today.
Then the landscape shifted. Android Automotive emerged, offering openness, services, and an app ecosystem that OEMs quickly recognised as the future for infotainment and connected platforms. It wasn’t a slow evolution – it was a wave, and it was clear that cockpit programs would increasingly be shaped by this new ecosystem.
For us, the challenge was immediate and personal: how do we preserve the precision and trust we had built with Kanzi, while embracing a platform designed with very different priorities?
Bridging Two Worlds
The first lesson was cultural, not technical. Our Kanzi engineers thought in terms of determinism and fault tolerance; our Android engineers thought in terms of flexibility and scale. To make these worlds meet, we had to encourage a new mindset – one that valued both safety-critical discipline and rapid, app-driven iteration.
From there, we began to reimagine our workflows. Instead of isolating Kanzi and Android, we experimented with ways to synchronise them across multi-screen cockpits – using shared state and event channels to avoid visible lag between cluster, HUD, and infotainment displays.
We asked ourselves: How do you ensure a driver sees the same design language across a cluster, a HUD, and an infotainment screen, even when they’re powered by different engines? That question became a guiding principle.
Learning Through Change
Of course, it wasn’t simple. Synchronisation raised questions of timing, resource management, and safety fallbacks. But each challenge forced us to innovate. We adapted our testing practices to account for two platforms instead of one.
We also embedded LiLA, our in-house agentic AI platform, into these workflows. LiLA automates key parts of verification and validation: generating test cases, writing executable test scripts, analysing defects, and compiling compliance-ready reports. What once required weeks of engineering effort can now be compressed into days – without compromising traceability, audit-readiness, or safety standards.
These industry advancements have also expanded the potential of Kanzi itself. The latest Kanzi One platform integrates generative-AI-powered tools for rapid HMI design and supports on-device AI execution, enabling designers and engineers to accelerate prototyping while maintaining production-grade performance and safety. These capabilities further strengthen Kanzi’s role in hybrid cockpit environments, complementing Android and other modern software stacks.
Validation also extended beyond software into the HMI itself. Our Verification & Validation teams use touch automation to replicate real driver inputs across multiple displays, ensuring consistent behaviour under varied conditions. This capability allows us to uncover issues that purely software-driven tests might miss and shortens the cycle from defect discovery to resolution.
This shift didn’t replace engineering rigour – it amplified it. By allowing AI to take on repetitive but essential tasks, our teams could focus on higher-value challenges such as synchronisation, system stability, and user experience refinement.
We stopped seeing Kanzi and Android Automotive as rival approaches; we began treating them as complementary elements of the cockpit ecosystem.
The Inflection Point in Cockpit Software
McKinsey’s Technology Trends Outlook 2025 frames the rise of the software-defined vehicle (SDV) as one of the defining transformations of the decade. It highlights how over-the-air (OTA) updates, AI-driven features, and scalable digital platforms will shape competitiveness. BCG, in its Automotive Suppliers at a Crossroads paper, reinforces this by warning that suppliers who fail to adapt to multi-platform ecosystems will struggle to stay relevant.
The message is clear: cockpit software is no longer a supporting feature. It is the frontline of differentiation. And it must be built on ecosystems that are flexible, secure, and scalable.
Looking Outward
Those external signals mirror what we’ve experienced internally: the cockpit is now an ecosystem, not a silo.
For OEMs, a hybrid Kanzi–Android approach means programs that can scale across premium and cost-sensitive vehicle lines while reducing duplication of effort. It simplifies platform strategy and reduces development risk.
For drivers, it means experiences that are visually rich, responsive, and continuously updated – bringing the benefits of Android’s ecosystem – while still retaining the confidence of deterministic, safety-critical cluster rendering. It is the best of both worlds: reliability and novelty in a single cockpit.
Evolution, not abandonment
Our story is one of evolution, not abandonment. Rather than choosing between Kanzi and Android Automotive, we built bridges between them. We invested in people, experimented with new workflows, and integrated AI as a co-pilot in our engineering journey – always keeping stability and safety as our north star.
That journey continues. And it is what gives us the confidence to say: whatever is the cockpit strategy of the OEM, we are ready to deliver engaging HMI experiences.
Anil S is VP Engineering at Acsia.
