Automotive

Drive-and-play gamification platform for premium EV brand

The client aimed to differentiate its vehicles in a crowded market by turning driving data into an engaging, software-defined experience that increases user retention and brand visibility.

Intellias developed a scalable in-car gamification platform that transforms vehicle telemetry into real-time insights and interactive feedback, promoting safer and more efficient driving.

Business outcomes:

• Up to 50–70% faster rollout – reduced development effort across multiple vehicle models through a reusable integration layer
• Stronger brand visibility – social sharing mechanics turn drivers into active brand ambassadors, generating organic reach
• Improved driving efficiency – measurable gains in eco-driving performance (kWh/100 km optimization) supporting ESG goals

Integrating Rust-based applications with AUTOSAR Classic environment

Intellias, in cooperation with HighTec and Vector, modernized embedded automotive software by migrating time-critical ultrasonic sensor software components (SWCs) from C to Rust, ensuring compatibility with AUTOSAR Classic stacks and legacy components. The solution enabled seamless integration into the existing environment, allowing memory-safe Rust applications to interoperate with C without compromising performance or system integrity.

Business outcomes:

• Seamless Rust–C interoperability – enabled stable cross-language integration within AUTOSAR Classic environment
• Improved software safety – ensured compliance with AURIX memory and safety requirements for embedded systems
• Reliable system communication – enabled consistent data exchange between Rust-based and legacy C-based SWCs

AI-based closed loop code generation for map compiler

Map compilation requires significant engineering effort when introducing new data formats. The client aimed to explore AI-driven code generation, from assisted development to automated closed-loop workflows.

Intellias developed an AI-based architecture to generate and refine compiler code with full contextual awareness. The approach was validated by generating a real map compiler module (POI, Roads) with NDS map data format.

Business outcomes:

• Fast PoC delivery – working solution delivered in 3 weeks with real map output
• Reduced effort and time – up to 40% reduction in development for new data formats
• Scalable approach – proven and reusable architecture for future map compilation components

Generative AI and knowledge graph services for efficient map production

To address slow and error-prone manual validation across a complex map production ecosystem, Intellias implemented a GenAI-powered solution that automates validation and streamlines workflows through the intelligent AI assistant.

Business outcomes:

• Faster validation cycles – replaced manual search and cross-checking across 4,000+ map entities with a unified AI assistant
• Improved consistency and quality – automated validation using MLflow pipelines and golden datasets, reducing variability and human error
• Scalable platform foundation – evolved from MVP to an architecture designed to support 1,000+ daily active users

Map Scout: Agentic AI solution for dynamic maps update

Traditional map updates rely on slow, scheduled data sources, creating a gap between real-world conditions and what drivers see, especially dynamic events like accidents, road closures, or hazards.

Intellias developed Map Scout, an AI-powered solution that continuously captures and validates real-time events from open sources, enabling faster and more accurate map updates.

Business outcomes:

• Stronger competitive edge – real-time intelligence outperforms traditional batch-based mapping updates
• Improved map accuracy and reliability – automated event extraction, geolocation, and confidence scoring ensure higher data quality
• Regulatory readiness – supports low-latency detection of safety-critical events, aligning with emerging standards such as Euro NCAP 2026 Local Hazards

AI-driven feedback flow: From in-car recordings to Jira tickets

The client required direct insights into user experience within their navigation app and needed a scalable way to capture and process real driver feedback.

Intellias implemented an AI-powered feedback system that captures audio and screen input directly from the vehicle, automatically processes it, and converts it into structured Jira tickets.

Business outcomes:

• Faster feedback processing – automated transcription, summarization, and ticket creation significantly reduce manual effort
• Improved product insights – real-time, structured user feedback enables faster identification of issues and feature needs
• Operational efficiency – support teams spend significantly less time handling and processing feedback across growing user bases