rinf.tech

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Overview

$5,000+

Min Project Size

$25 - $49/hr

Avg Hourly Rate

250 - 999

Employees

2006

Year Founded

ABOUT RINF.TECH

Digital Products & Platforms, Automotive, Embedded

Founded in 2006 and based in Bucharest, Romania, rinf.tech is a global technology partner with offices and delivery centers throughout Europe, North America, and Asia. The company specializes in enterprise AI capabilities, innovative research and development solutions, and custom software product engineering. Its key areas of expertise include digital products and platforms, automotive software engineering, embedded systems, cloud-native modernization, and AI-driven innovations such as machine learning platforms, agentic AI, generative AI using PyTorch/TensorFlow, natural language processing, and computer vision. rinf.tech offers a wide range of services and has a team of over 600 technology professionals, including dedicated AI, digital, and embedded specialists. The company has successfully completed more than 1,000 projects for Fortune-class enterprises as well as mid-sized companies, and it has been recognized as a leading AI development firm in Bucharest.

Languages Spoken

EnglishRomanian

HIGHLIGHTS

$5,000+

Min Project Size

$25 - $49/hr

Avg Hourly Rate

250 - 999

Employees

2006

Year Founded

Services

Focus

Industries

Clients

Services Provided+1 Services

18% Backend Development

10% QA & Software Testing

13% API Development & Integration

10% Custom Web Application Development

12% Custom AI Chatbot Development

5% IT Staff Augmentation

12% Machine Learning Model Development

10% AI Strategy & Roadmap Consulting

Portfolio

Low-level Drivers for Automotive MCU

Unknown

**Client**: Automotive Tier 1 Technology **Focus**: C embedded, JTAG debugging, Python Services **Activities**: - Initiating board bring-up for new MCUs - Developing low-level drivers and features - Software integration - Conducting software integration testing and releases **Challenges**: - A new MCU family designed for the automotive sector. - Development of over 10 drivers and tools to assist automotive integrators in creating solutions with the new MCU. - Lack of bandwidth for the release of the new MCUs, necessitating assistance to accelerate development and testing within a highly aggressive timeline. **Solution**: We played a vital role in creating toolkits for developers. Our efforts were in collaboration with a leading semiconductor company that serves over 25,000 customers. We addressed intricate challenges, such as developing low-level drivers essential for the seamless functioning of next-generation products upon their market launch, ensuring that these product suites remain competitive within the automotive sector. **Key Areas of Expertise**: - **Board Support Package**: - Complete bring-up of new MCUs, specifically the NXP iMX8 DX. - Implementation of low-level drivers, including display handlers, light sensors, orientation sensors, QNX raw NAND drivers, and optimizations for startup and inter-processor communication. - Providing software workarounds for MCU errata. - **Low-Level Features**: - Control of touch displays via low-level drivers on QNX and firmware update support. - **Software Integration**: - Integration of software from India and Timisoara. - Adaptation and enhancement of the build system. - **Software Integration Testing and Releases**: - Defining integration tests. - Measuring software KPIs. - Conducting integration tests in alignment with customer deadlines. - Improving the release process. **Results / Contributions**: - Successfully built a new MCU family within the specified timeline without compromising quality. - Developed over 15 sample use cases that enabled clients to accelerate the creation of new automotive products. - Provided several complementary libraries that helped our customer expand into new ecosystems and attract additional clients. - This support allowed our customer to seize market momentum and explore new business opportunities.

HIL Automation Testing

Unknown

Client: A Global Manufacturer of Agricultural Equipment Technology: - Software Tools: MATLAB, Simulink, Vector CANoe, TwinCAT - Programming/Scripting/Automation Languages: Python, CAPL - HIL Hardware: dSPACE, Speedgoat, Beckhoff, Vector VN Series Services: - HIL Design: Electrical diagrams, HIL block diagrams, and assembly support documentation (HW) - Manual Testing: HIL setup and maintenance; test case (TC) creation; execution of manual test cases - Automation Testing: Automated HIL testing (creation and execution of automated test scripts) Solution: Rinf.tech's specialists helped the client enhance their assessment of financial risks, make informed strategic investments, and improve testing capabilities through new workflows and increased productivity in the Validation area. Key initiatives included: - Optimizing the software testing process (utilizing the V-model) - Developing a mini HIL environment for manual testing (software and hardware validation) - Establishing HIL for automation testing (software and hardware validation) - Standardizing the validation process (using Siemens Polarion) - Conducting automation testing (executing automated test scenarios) - Creating automated tests (using CAPL and Python) Rinf.tech has proven to be a reliable partner in software and hardware validation, ensuring high-level quality assurance through advanced engineering expertise. Results (Team Achievements): - Two ECUs tested using a single common test bench - Additional test cases created, resulting in a 35% automation coverage (test case creation and automation processes in validation using Agile development) - A 40% increase in testing capabilities, supporting the scalability of the client’s business through comprehensive assistance with test case creation and automation processes via Agile development. - Clients have direct access to Rinf.tech’s experts, enabling them to better evaluate financial risks, make strategic investments, and enhance testing capabilities through innovative processes and increased productivity in the Validation area. Complete Case Study:

Instrument Cluster for Mainstream Vehicles

Unknown

Client: A leading global automotive Tier 1 supplier. Technology: AUTOSAR architecture; software development in C/C++; dual MCU system with ARM cores; inter-processor communication (IPC); design of two boards (intelligent and front-end) APX; OSEK RTOS; Green Hills Integrity RTOS supporting separate VAS and memory protection safety functions; MOST (Media Oriented System Transport) integration with the infotainment system; high-speed CAN connection; and Open GLE graphics. Services provided: Cockpit electronic products, including digital instrument clusters, information displays, infotainment systems, head-up displays, telematics, cockpit domain controllers, and platforms for autonomous driving. Challenges faced: Managing two instrument cluster projects for two leading global automotive manufacturers, addressing 1600 defects, implementing over 28 features, and navigating a completely distributed environment where communication and synchronization with other teams were vital. There was a lack of clarity regarding specifications and technologies at the project kickoff. Solution: Our team, in collaboration with the client’s mirror team, undertook the responsibility of delivering the next generation of instrument clusters for a major global automotive brand. We achieved this by prioritizing quality development and integration, which enabled the client to pursue additional business opportunities with our support. RINF TECH’s team contributed by: - Software development in embedded programming using C - Integration of AUTOSAR modules - Bringing up hardware for new instrument clusters - Utilizing Vector tools for AUTOSAR. Results: - Over 1600 issues resolved - More than 38 new features developed - Deployment time reduced by 50% thanks to effective ramp-up and knowledge transfer - 100% compliance with the client’s tools, standards, processes, and methodologies. For a complete case study, visit: https://www.rinf.tech/how/industries/automotive/instrument-cluster-for-m...

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