ThreeV builds an inspection automation platform using custom vision models, LLMs, and spatial computing to analyze physical assets in power, utilities, renewables, and aviation. The stack—Python, Kafka, AWS/Azure, Kubernetes, SAP, GIS—reflects a data-intensive, multi-cloud infrastructure strategy. Heavy hiring in senior and principal engineering roles across Peru, US, and Colombia signals rapid scaling of core ML and platform capabilities to handle real-time data pipelines and inference at scale.
ThreeV Technologies develops an inspection automation platform targeting asset-heavy sectors including power utilities, renewable energy, public infrastructure, and aviation. The platform combines custom large vision models with LLMs to automate asset inspections, reduce operations and maintenance costs, improve data accuracy, and prevent failures. The company operates from Los Angeles and employs 2–10 people, with active engineering hiring across multiple geographies. Core technical work centers on real-time data pipeline design, multi-cloud infrastructure (AWS/Azure), SAP and GIS integrations, and scaling AI inference for production workloads.
Python, Kafka, AWS, Azure, Kubernetes, SAP, GIS, shadcn/ui, Radix UI, Tailwind CSS, Storybook, ChatGPT, and Claude. Infrastructure spans multi-cloud (AWS/Azure) with Kubernetes orchestration.
GIS and SAP integrations are part of the inspection platform's data pipeline architecture, enabling legacy system integration and spatial data processing for infrastructure asset analysis.
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