AI-powered EV grid flexibility platform with GPU inference at scale
Tether pairs EV charging prediction with real-time grid optimization using Node.js, Kubernetes, and NVIDIA H100/H200 GPUs. The tech stack and project list reveal a company pivoting from vehicle-grid coordination toward managed inference services and large-scale video/multimodal AI—a wider ambition than the LinkedIn mission statement suggests. Engineering-heavy hiring (12 of 15 active roles, mostly senior) and pain points around GPU scaling and data pipelines confirm they're building infrastructure, not just SaaS.
Tether uses machine learning to predict EV charging patterns and coordinate parked vehicles as a distributed battery resource for grid stability and demand response. Founded in 2022 and based in Stockholm, the company operates as a 2–10-person team with aggressive hiring velocity (7 roles posted in the last 30 days, 15 open). The platform addresses two customer segments: grid operators seeking flexibility reserves, and EV owners seeking to monetize idle capacity. Current engineering focus spans charging optimization, real-time monitoring dashboards, and foundational AI infrastructure—particularly GPU-accelerated services and multimodal data pipelines.
Node.js for backend services, Kubernetes for orchestration, NVIDIA H100 and H200 GPUs for inference, React Native for mobile, and iOS/Android native apps. They're also exploring Bitcoin mining for excess grid power optimization.
Managed inference services, GPU-accelerated cloud platforms, real-time monitoring dashboards, multimodal and video research, and large-scale automated data acquisition pipelines for AI model training.
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