Positron ai Headquarters & Office Locations

Positron ai (Private) is headquartered in Reno, Nevada, United States. Founded in 2023, the company operates across 1 countries with approximately 37 employees worldwide.

Where is Positron ai's main office?

Positron ai's main headquarters office is located at Reno, Nevada, USA, Reno, Nevada 89501. This serves as the company's primary corporate address and is home to its executive leadership team.

Positron ai regional offices

Beyond its headquarters in Reno, Positron ai maintains 4 offices across 1 countries. Regional offices span 1 countries.

Positron ai contact information

The main switchboard for Positron ai headquarters can be reached at 510-365-2166. For investor relations, visit positron.ai/investor-relations.

What does Positron ai do?

Positron is an artificial intelligence infrastructure company that designs and supplies purpose-built hardware and software systems for accelerating inference of transformer-based models used in generative AI workloads. Its offerings include inference-optimized compute platforms that support deployment of large language models and other AI applications with reduced power consumption and enhanced performance compared with traditional GPU-based systems, enabling enterprise and cloud teams to serve models efficiently with lower operational cost and energy use. The company’s technology is engineered to run popular open-source transformer models seamlessly through compatible APIs, facilitating integration into existing AI workflows without extensive modification. Positron’s platforms combine custom hardware architectures with supporting software to help customers scale AI deployment, manage performance, and extend model context capacity for diverse workloads. It also works to advance next-generation compute solutions that address memory bandwidth and scalability challenges common in AI inference environments. Positron engages with technical and infrastructure teams to deploy its systems in data center and cloud environments where inference workloads require cost-effective, high-throughput processing.