VLM Run builds enterprise infrastructure for visual intelligence. Its unified API converts images, PDFs, screenshots, presentations and video into schema-conformant JSON for downstream analytics, indexing and automation, spanning OCR, tagging, captioning, extraction, recommendations and visual search. The company also offers vertical model specialisation: fine-tuning and hardening vision-language models for specific industries and use cases in hours, supported by evaluation and reliability controls intended to meet production SLAs. Deployments can run in customers' private cloud or VPC with strong isolation and data controls.
Technical work spans computer vision, vision-language models, production ML infrastructure, robotics, OCR, structured data extraction, model fine-tuning, evaluation and reliability engineering, visual search, and privacy-preserving deployment. Engineering practice is test-driven and evals-driven, and the workflow is AI-native: tools such as Devin, Cursor and Claude Code write more than 30% of the company's code.
The founding team has decades of combined experience in computer vision, robotics and production ML infrastructure, with backgrounds spanning Toyota Research, AWS AI Labs and MIT/CMU, and has shipped systems for autonomous vehicles, production ML and large-scale VLM deployments. The company is venture-backed by Silicon Valley and New York investors and has a presence in both regions. Industry verticals include autonomous vehicles, enterprise visual intelligence and production ML.
