We are a leading provider of Product Engineering Services, offering expertise in Semiconductor design, Multimedia & Imaging, Connectivity, Cloud & Enterprise solutions, and Machine Learning & Deep Neural Networks. With a commitment to excellence, our ISO 9001:2015 and ISO/IEC 27001:2022 certifications attest to our dedication to maintaining the highest standards of quality assurance and process compliance across all aspects of our Product Engineering Services.
Our Offerings
SEMICONDUCTOR
Silicon engineering done the old-fashioned way. Backed by state of the art tools and methodologies.
SOFTWARE
Assembly language to Applications.
And everything in between. Full-stack – truly.
Testimonials
We have partnered with Ignitarium over the past two years on the delivery of kernel code and optimized neural networks for our runAI and speedAI families of AI inference products. Their team has integrated effortlessly with ours, assisting in the delivery of essential software products to our customers.
Senior Manager AI Chip MakerWe partnered with Ignitarium for Device Driver validation for our Battery Management System (BMS), targeting the needs of the next-gen EV segment. The team took up the ownership of planning the tasks, creation of test plans and test cases and eventually execution of these to ensure the requirements are fully covered during the validation cycle. The engineers working on the project were technically competent, transparent and were able to adapt to the dynamic needs of our team.
DIRECTOR, Automotive Software group Tier-1 Semiconductor company specialized in design & manufacture of high-performance ICsIt has been a real pleasure working with the Ignitarium team. The quality of the team that worked on verification and modelling of our ARM based wireless SoC project helped us to meet our tape-out timeline. They understood the design requirements, and performed the necessary tasks well and in a thoroughly professional manner. We really appreciate the help and support you have given to us and the flexibility you demonstrated at various critical points of the project.
Thomas Varghese MD & VP - Engineering, LifeSignalsIgnitarium has been instrumental in the development of our RoC chip including the design of complex DSP IPs and sub-systems. Their team has contributed significantly to the Functional Safety Architecture, Design and Verification of the ARM Cortex-R5F based CPU subsystem that forms the primary control engine of this chip; this was particularly critical since this chip is targeted towards ASIL compliance. I’m happy to endorse Ignitarium’s capability in ISO:26262 based safety critical silicon design.
VP-Engineering US-based Automotive chip companyNews & Views
Ignitarium adds New Member to its Board of Directors
Ignitarium has expanded its board of directors with the appointment of Mr. Sudip Nandy, former MD of ChrysCapital and ex-Chairman of Aricent.
Automotive Infotainment Services: Enhancing the In-Car Experience
Automotive infotainment services are a critical part of modern vehicle design, providing a seamless blend of entertainment, communication, and navigation systems.
Graph Neural Networks Demystified: How They Work, their Applications and Essential Tools
Graph Neural Networks (GNNs) are a powerful type of deep learning model designed to handle data in the form of graphs. Unlike traditional methods, which work well with data represented in grids or sequences (like images or text), GNNs are specifically suited for tasks where data is interconnected.
Ignitarium adds New Member to its Board of Directors
Ignitarium has expanded its board of directors with the appointment of Mr. Sudip Nandy, former MD of ChrysCapital and ex-Chairman of Aricent.
Automotive Infotainment Services: Enhancing the In-Car Experience
Automotive infotainment services are a critical part of modern vehicle design, providing a seamless blend of entertainment, communication, and navigation systems.
Graph Neural Networks Demystified: How They Work, their Applications and Essential
Graph Neural Networks (GNNs) are a powerful type of deep learning model designed to handle data in the form of graphs. Unlike traditional methods, which work well with data represented in grids or sequences (like images or text), GNNs are specifically suited for tasks where data is interconnected.
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