AI deployment platform for sovereign, multi-cloud infrastructure
UbiOps provides deployment and management infrastructure for production AI workloads across on-premise, hybrid, and multi-cloud environments. The stack—Python, Kubernetes, Terraform, Ansible, plus virtualization primitives (KVM, Proxmox, QEMU)—reveals a company solving infrastructure orchestration at depth rather than just wrapping cloud APIs. Pain points around vendor lock-in, hybrid environment management, and air-gapped reliability indicate a wedge into regulated industries where infrastructure sovereignty matters more than off-the-shelf convenience.
UbiOps builds a platform for deploying and scaling AI workloads on customer-controlled infrastructure. The company serves organizations that require on-premise or hybrid-cloud deployment options and want to avoid vendor lock-in on cloud providers. Founded in 2020, the team is small (11–50 employees) and engineering-focused, with active projects spanning installation automation, hybrid deployment workflows, and customer AI solution implementation. The platform abstracts away orchestration complexity across Kubernetes, containerization, and infrastructure-as-code tooling, enabling data science and ML teams to move models into production without managing deployment infrastructure directly.
AWS, GCP, and Azure, plus on-premise and hybrid deployments via Kubernetes, Terraform, and containerization. The platform also supports air-gapped environments.
Backend and orchestration: Python, Django, Go, Kubernetes, Docker, Terraform, Ansible, Helm. Database: PostgreSQL. Frontend: React. Infrastructure: GCP, AWS, Azure, plus KVM, Proxmox, QEMU for virtualization.
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