Build your data foundation for AI-powered business growth

Automotive Data Services

Transform how you manage, monetize, and use data in the AI era

Automotive data analytics services help OEMs, Tier 1 suppliers, and mobility providers turn connected-vehicle, infrastructure, manufacturing, and customer data into a foundation for AI-driven transformation. In the AI era, structured and efficiently utilized data becomes one of the strongest competitive advantages. With a targeted data strategy, governance, and AI readiness approach, automotive companies can unlock new value from vehicle operations, software performance, customer behavior, fleet usage, production quality, and real-world driving insights.

Intellias automotive data services help companies build a strong data foundation through scalable data pipelines, data collection and transformation, closed-loop validation, AI-enhanced analytics, and standards-based data engineering. We turn raw automotive data into actionable intelligence, helping clients reduce time to insight, improve data accuracy, increase AI readiness, and make data a practical growth engine for mobility businesses.

Trusted by leading companies worldwide

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Automotive data services

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Data strategy

Define how data supports your business goals, AI ambitions, and mobility product roadmap through the right governance, technology, and analytics approach.

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Data management

Keep automotive data accurate, secure, governed, and accessible across its lifecycle to support trusted decisions and scalable operations.

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Data engineering

Build scalable data pipelines, architectures, and processing systems that turn raw vehicle, infrastructure, and enterprise data into high-quality datasets for analytics and AI.

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Data analytics

Analyze high-volume data from vehicles, users, fleets, and mobility ecosystems to enable predictive maintenance, route optimization, behavioral insights, and product improvement.

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BI & reporting

Turn complex automotive data into clear dashboards, visualizations, and performance reports that help teams act faster and make better decisions.

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DataOps

Apply agile and DevOps practices to data workflows to improve speed, automation, quality, and reliability across the full data lifecycle.

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Data commercialization

Transform internal data assets into monetization solutions, services, and insights that open new revenue opportunities for OEMs, Tier 1s, and mobility companies.

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AI-ready data

Organize, enrich, and validate high-quality data to build reliable, scalable, and business-ready AI systems.

Clear outcomes: Our clients’ stories

Intelligent parking monitoring solution for real-time occupancy insights

To enable real-time access to parking lot occupancy data via web and mobile applications, Intellias upgraded the client’s existing parking infrastructure with a smart monitoring system. The solution integrated LoRaWAN wireless parking sensors, LoRaWAN-LTE gateways, existing gates, wired sensors, parking guidance screens, and camera-based license plate recognition into a centralized Azure-based platform for data processing, visualization, and infrastructure control.

Business outcomes:

  • Lower hardware investment – upgraded the parking monitoring system by reusing existing infrastructure instead of replacing gates, wired sensors, and guidance screens
  • Real-time occupancy visibility – enabled live parking data collection from multiple sensors and systems for web and mobile applications
  • Future-ready integration architecture – simplified future hardware upgrades through flexible microservices, MQTT-based communication, and reverse-engineered RS485 protocol integration

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 data 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

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

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

Our automotive data accelerators for AI-enabled services

At Intellias, we build accelerators that help OEMs and Tier 1 suppliers test, modernize, integrate, and bring products to market faster without engineering everything from scratch. From next-generation infotainment systems to autonomous driving solutions, our accelerators simplify complex transformations into efficient and scalable implementation of validated industry-grade solutions.

Intellias automotive accelerators showcase our cross-domain expertise, built through collaboration with clients, technology partners, industry associations, and open-source communities. They address key areas where organizations need tech innovation and business efficiency from a proven automotive data analytics company, spanning advanced data capabilities, cloud connectivity, enhanced user experience, embedded development, and modern platforms.

IntelliKit

The Automotive Portable Kit, or simply IntelliKit, showcases the engineering expertise we provide to our clients by integrating automotive-grade hardware, navigation systems, cloud platforms and tools, developing embedded and middleware software, and designing breathtaking user interfaces.

Supply Chain Intelligence Layer

An AI-powered accelerator showcasing a modular, agent-based system for predictive supply chain management. This solution seamlessly integrates with existing TMS, enriching them with data-driven insights from real-world events.

Agentic AI Traffic Assistant

A map-centric AI-powered assistant provides access to real-world traffic, routing, and incident data through conversational interfaces and live map visualizations. It transforms fragmented data into actionable insights for operators, planners, and business users, enabling natural language interaction via text and voice.

Map Compilation Accelerator

Intellias Map Compiler accelerates the compilation of map data in various formats into NDS.Live, allowing businesses to integrate updatable, reliable, and accurate online maps into their products and services.​

AI-driven engineering services for future mobility

Intellias takes a strategic approach to advancing AI adoption for clients and within its own organization. We design, implement, and optimize AI strategies, delivering AI-powered engineering services that solve real-world problems and generate measurable results.

We leverage composable AI agents, modular, purpose-built tools integrated directly into the SDLC, where they deliver the highest productivity levels. For our partners, this translates into faster time to market, reduced costs across development and validation phases, and more efficient end-to-end delivery of automotive AI data services.

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AI strategy and adoption

Designing, implementing, and optimizing mature AI strategies for mobility organizations, from simple AI as an assistant to scaled AI orchestration.

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Composable AI agents across the SDLC

Deploying modular AI agents for requirements analysis, architecture design, code generation, test generation, verification, validation, and compliance support.

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AI integration with existing toolchains

Implementing AI into established engineering environments through static data and dynamic MCP-based integrations, without disrupting proven workflows or governance.

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AI automation for ASPICE V-model

Applying AI-driven tools to automate V-model processes from requirements to qualification, ensuring ASPICE compliant development and maintenance, utilizing cloud- and model-agnostic AI platform.

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Human-in-the-loop AI engineering

Combining AI productivity benefits with expert human supervision to ensure safety, quality, and engineering discipline across mobility programs.

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AI accelerators for mobility use cases

Running active AI accelerator programs for infotainment testing, LLM-based verification and validation, intelligent map data management, and closed-loop code generation for mobility platforms.

Automotive data services for AI-enabled mobility

Turn your automotive data into a trusted foundation for AI-driven solutions

Let’s talk

Partnerships and certifications

Ecosystem provider partnerships
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Compliance with industry standards
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What our clients say

Bart Sweerman
Senior VP, Global Services & Support at HERE Technologies
Bart Sweerman  1
Eugene Feld
VP of Engineering at MileMaker
Eugene Feld 1
Cesar Arego​
Business Development Manager, Automotive Digital Cockpit​ at TomTom
Cesar Arego

In-focus mobility domains

Intellias automotive data services FAQ

Automotive data analytics services help OEMs, Tier 1 suppliers, and mobility companies collect, process, analyze, and activate data from vehicles, users, infrastructure, manufacturing systems, and business operations. These services turn raw automotive data into actionable insights for better decision-making, improved product performance, AI readiness, and new business value.

Automotive data and analytics services use data from connected vehicles, in-vehicle systems, sensors, manufacturing and IoT platforms, supply chains, dealer networks, aftersales operations, customer experience channels, fleet systems, and mobility infrastructure. By combining these sources, companies can create a unified data foundation for advanced automotive data services, predictive analytics, and AI-powered use cases.

OEMs and Tier 1 suppliers use data analytics services in the automotive industry to improve vehicle quality, monitor software performance, optimize manufacturing, predict maintenance needs, enhance navigation and routing, personalize in-vehicle experiences, and understand driver behavior. With automotive data insights services, companies can move from fragmented data to faster decisions, better products, and more efficient operations.

AI is used to detect patterns, predict failures, automate validation, support ADAS and software-defined vehicle development, improve fleet intelligence, analyze customer behavior, and enhance digital cockpit experiences. Automotive AI data services also help prepare, enrich, validate, and govern data so AI models can work with accurate, trusted, and scalable datasets.

Secure automotive smart data services require clear data governance, role-based access, encryption, data quality controls, anonymization or pseudonymization, and compliance with regulations such as GDPR and data sovereignty requirements. For OEMs and Tier 1 suppliers, this means building data ecosystems where sensitive vehicle, user, and operational data can be used responsibly while remaining protected and traceable.

Choose an automotive data analytics company that combines automotive domain expertise, strong data engineering capabilities, AI readiness experience, cloud and platform knowledge, and a clear understanding of compliance, security, and industry standards. The right provider should help you build scalable data pipelines, improve data quality, create actionable insights, and turn automotive data into a long-term business asset.