Hanwha and Ambarella Sign $800 Million Edge AI Partnership
Hanwha and Ambarella announced a long-term agreement worth over $800 million in potential revenue spanning more than a decade. The deal covers co-development and sourcing of edge AI chips and software across Hanwha's robotics, industrial automation, video security, and life sciences divisions.
The partnership represents one of Ambarella's largest deals to date. Ambarella reported fiscal 2026 revenue of $390.7 million, with IoT revenue growing 50% year-over-year as edge AI adoption accelerates across enterprise security and portable video applications.
What the agreement covers
Hanwha Vision will integrate Ambarella's edge AI processing capabilities with its own expertise in image processing, analytics, and cybersecurity. Hanwha Vision retains full control over its proprietary Wisenet SoC, which it has developed internally since 2010.
Ambarella's platform includes an installed base of 46 million AI units across 12 different edge AI chips. The chips deliver performance ranging from compact AI cameras to high-performance multi-sensor systems for robots and autonomous machines, all built on the company's proprietary CVflow AI accelerator architecture.
The agreement's multi-generational structure lets both companies align technology roadmaps and accelerate product development cycles. The Cooper Development Platform provides tools and resources for developers to build and deploy solutions across product families.
Why this matters for product teams
Long-term chip partnerships like this one signal how hardware and software vendors now plan product releases years in advance. For product managers and engineers, this means clearer visibility into component availability and performance roadmaps.
The deal also shows how edge AI is moving beyond security cameras into robotics and industrial automation. Companies developing products in these categories can expect more specialized chips optimized for specific workloads rather than generic processors.
Ambarella's platform supports CNN models, generative AI frameworks, and agentic systems-the types of AI approaches product teams are increasingly asked to integrate into hardware products. Access to optimized silicon for these workloads reduces the engineering burden of deploying AI at the edge.
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