Qoria operates a distributed monitoring and risk-detection platform for child digital safety, built on GCP + Azure + AWS with Go, Java, and Python microservices running on Kubernetes. The tech stack reveals heavy investment in data infrastructure (BigQuery, Bigtable, CockroachDB, Kubeflow, high-performance ingest pipelines) paired with deployment automation (Terraform, ArgoCD, Cloud Build) — indicating the company is scaling from school deployments toward real-time behavioral analysis at scale. Current hiring is balanced across engineering, product, and data, with 11 open roles suggesting active buildout of analytics and deployment capabilities.
Qoria is a Perth-based public company serving schools, families, and education institutions with tools to monitor and identify at-risk student behavior across digital platforms. The product spans managed services (Smoothwall Monitor), school ecosystem deployments (Linewize), and cloud-native risk-detection features. Core challenges center on identifying behavioral risk signals, protecting against harmful content, maintaining secure network integration, and streamlining the sales and customer success workflows that support multi-stakeholder adoption (schools, parents, students). The company is headquartered in Australia with hiring activity in Australia and Spain.
Qoria runs on GCP, Azure, and AWS with Go, Java, Python, and C# across Kubernetes clusters. Data processing uses BigQuery, Bigtable, CockroachDB, and Kubeflow for real-time analysis. Infrastructure is managed via Terraform and ArgoCD.
Current projects include Linewize ecosystem school deployments, Smoothwall Monitor managed services, high-performance data ingestion pipelines for global activity monitoring, and deployment process improvements across engineering and sales teams.
Qoria'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.