ONIQ builds a Lean-focused analytics platform for manufacturing operations teams, using Python + Pandas + Polars on cloud infrastructure (GCP, Azure, AWS, Kubernetes) paired with a React + TypeScript frontend. The hiring mix reveals a manufacturing-first go-to-market: 3 roles in operations/manufacturing alongside 1 engineering hire, suggesting field-driven customer engagement rather than pure product-led adoption. Active projects center on customer rollouts, data visualization at scale, and converting pilot engagements into SaaS contracts—aligned with their stated challenge of driving platform adoption.
ONIQ is a 11–50 person company founded in 2020 and headquartered in Cologne, Germany. The platform—branded as IQA Lean Copilot—analyzes production performance data to identify inefficiencies and recommend continuous-improvement actions, positioning Lean methodology as a software system rather than a manual practice. The technical architecture spans Python data pipelines (Dagster, FastAPI) and a modern web stack (React, TypeScript, Cypress) deployed across cloud providers. Customer engagement centers on converting pilot deployments into long-term contracts, with operations and marketing teams actively scaling demand generation and adoption support.
Frontend: React, TypeScript, Jest, Vitest, Storybook, Cypress. Backend: Python, FastAPI, Dagster. Data: pandas, NumPy, Polars. Cloud/DevOps: GCP, Azure, AWS, Kubernetes, Terraform, OpenTofu, Pulumi.
Current projects include SaaS product rollout, scalable web app development, data visualizations for large production datasets, analysis workflows, and a B2B demand-generation engine to convert pilot customers into long-term partnerships.
ONIQ's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.