Engineering the Intelligent Vehicle Stack
Driving the Software-Defined Revolution
The automotive ecosystem is shifting fast - shaped by rising expectations around safety, connectivity, and cybersecurity, and mounting pressure on OEMs to reduce recalls, speed up integration, and simplify software delivery. This shift is driving a fundamental rearchitecture of vehicles as modular, upgradable software platforms.
At Innobox, we engineer Software-Defined Vehicles (SDVs) across the full lifecycle - from platform abstraction and middleware integration to containerized application deployment and in-the-loop validation. Aligned with centralized E/E architectures, service-oriented design, and continuous delivery pipelines, we help OEMs, Tier-1s, and semiconductor partners co-create the next generation of connected, intelligent mobility.
Impact Across the Ecosystem
Software-Defined Vehicles are redefining the way we build, update, and experience transportation - turning cars into dynamic, data-rich vehicle ecosystems.
For OEMs & Automotive Engineers, SDVs unlock:
Lower Bill of Materials (BoM)
Greater software reuse & standardization
Simplified hardware + software co-design
Faster time-to-market through intelligent modularity
For Drivers & End Users, SDVs enable:
On-demand features and personalization
Embedded cybersecurity with onboard AI
Predictive diagnostics & smarter vehicle behavior
Vehicles that evolve with you — continuously
Our Capabilities
We build the full software stack for SDVs — from intelligent middleware and containerized deployment to secure OTA and in-the-loop validation.
01
Development & Platform Engineering
Building the intelligent software core.
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Middleware & OS Abstraction
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Adaptive & Classic AUTOSAR
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DDS (Data Distribution Service), SOME/IP
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Service-Oriented Architecture: gRPC & REST APIs
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Operating Systems
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QNX, Yocto-based Linux, RTOS
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Android Automotive, AGL (Automotive Grade Linux)
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Communication & Data Models
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CAN, LIN, FlexRay, Automotive Ethernet
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COVESA VSS, DDS IDL, JSON/YAML
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BSPs, Drivers & Firmware
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Board Support Packages (BSPs)
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MCAL drivers
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Firmware development for Infineon, NXP, Intel, and Qualcomm architectures
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AI & Predictive Maintenance at the Edge
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Onboard inference engines: TensorRT, ONNX Runtime, PyTorch, TinyML
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Real-time anomaly detection and predictive analytics pipelines
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02
Application Deployment
Docker, LXC, Podman (on embedded Linux/AGL)
Hypervisors: ACRN, Xen, QNX
Secure and scalable for multi-domain applications
03
Connected Vehicles
Telematics Protocols: MQTT, CoAP, DDS
Device Management: TR369 (USP), TR069, OMA LwM2M
Cloud Integration: AWS IoT Core, Azure IoT Hub, Google Cloud IoT
Security Standards: TLS 1.3, DTLS, ISO 21434, IEEE 1609.2
V2X Communication: Wi-Fi, LTE, 5G, Bluetooth, and RFID support for smart infrastructure interaction
Sensor Fusion Integration: LiDAR, radar, and vision stream integration for perception-aware vehicle systems
04
Digital Cockpit Engineering
Driver Interfaces
Multi-display clusters, HUDs, and adaptive head units
IVI Systems
Android Auto, Apple CarPlay, voice assistants like Siri and Alexa
Shared Mobility & UX
Parking assist, HMI/UX design, and rear-seat display apps for ride-share and fleet applications
Application Software Solutions
Experience layers that extend the vehicle into everyday digital ecosystems.
AI/ML Models
Predictive maintenance, vehicle health, driver behavior, route optimization
Cloud-Native Experiences
Connected car experiences deployed on AWS, Azure, or Google Cloud
Mobile & Web Companion Apps
Native apps for vehicle control, status monitoring, personalization
APIs for Services Integration
Vehicle services APIs for third-party platforms, e-commerce, and digital ecosystems
Why It Matters More Than Ever
The automotive future is software-defined. Your choice of software partner will determine whether you lead or follow in this transformation.