Cloud Infrastructure & DevOps for AI Workloads

AI systems are only as reliable as the infrastructure they run on. A brilliant AI agent is useless if it crashes under load, takes minutes to respond, or loses data during deployment. Zoviq AI builds the cloud infrastructure and DevOps pipelines that keep your AI systems fast, reliable, and scalable.

We work primarily with AWS and Google Cloud Platform, designing architectures that handle the unique demands of AI workloads — GPU compute for model inference, vector databases for RAG systems, real-time data streaming for live applications, and cost-optimized scaling that keeps your cloud bill predictable.

What We Build

Cloud architecture designed specifically for AI. This includes compute infrastructure for model serving (GPU and CPU), vector database clusters for retrieval-augmented generation, object storage for training data and model artifacts, and networking configurations that minimize latency between services.

CI/CD pipelines that automate your entire deployment process. Code changes are tested, built, and deployed automatically with rollback capabilities. Your AI models and applications go from development to production safely and consistently, every time.

Kubernetes orchestration for containerized AI workloads. We set up and manage Kubernetes clusters that auto-scale based on demand — spinning up inference pods during peak hours and scaling down at night to control costs.

Infrastructure-as-code using Terraform and CloudFormation. Your entire cloud environment is defined in version-controlled code. This means reproducible deployments, easy disaster recovery, and no configuration drift between environments.

Canadian Data Residency

For businesses that need data to stay in Canada, we architect solutions using AWS Canada (Montreal) and GCP Montreal regions. Your data — including AI model inputs, outputs, and training data — stays on Canadian soil. Combined with encryption at rest and in transit, PIPEDA and Law 25 compliance is built into the infrastructure layer.

We also implement monitoring and alerting using Datadog, CloudWatch, or Prometheus and Grafana. You get real-time visibility into system health, latency, error rates, and resource utilization. When something goes wrong, your team knows about it before your customers do.

Book a free consultation to discuss your cloud and DevOps needs.