AI-powered quality inspection and process optimization for food manufacturers
Polysense deploys computer vision and machine learning to food production lines, automating quality control and linking inspection insights back to process parameters. The stack—Python, Kubernetes, Vue, GraphQL, multi-cloud (Azure/AWS/GCP)—reflects a mature ML ops infrastructure. Active hiring is concentrated in engineering (6 roles) with a parallel build in sales (4 roles) and support (2 roles), signaling expansion from product-market fit into customer success and upsell. Internal projects show a shift from vision-system deployment toward customer value scoping, upsell, and post-sale engagement—a sales org scaling playbook.
Notable leadership hires: Delivery Head
Polysense is an AI quality-control platform for food manufacturing. The product uses machine vision to inspect product quality on production lines and automatically adjusts process parameters based on findings, reducing material waste and cost. Founded in 2022 and based in Ghent, Belgium, the company operates with 11–50 employees. Revenue model centers on recurring software adoption across customer production lines. Current challenges include product consistency, customer adoption across multiple production sites, and churn prevention—typical pain points for B2B manufacturing software scaling past early reference customers.
Python, Kubernetes, Docker, Vue, TypeScript, Node.js, Nest.js, GraphQL, and multi-cloud deployment on Azure, AWS, and GCP. Auth0 and Azure AD handle identity.
Vision pipeline deployment, process-parameter optimization, customer value and upsell scoping, and post-sale customer success. Recent focus includes expanding adoption of their autocontrol product and transitioning from sales to customer success operations.
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