Azin bridges frontier reasoning models with mission-critical High Performance Computing, bare-metal GPU fabrics, and distributed schedulers to achieve zero-downtime, self-healing infrastructure autonomy.
The 5-stage continuous closed-loop pipeline powering Azin's autonomous high performance cluster orchestration.
Ingests distributed Slurm batch jobs, multi-tenant MPI queues, and training scripts with automated dependency resolution.
Evaluates multi-node topology constraints, NUMA locality, and predicts NVLink saturation patterns before dispatch.
Defragments contiguous GPU islands across physical racks, slashing node idle fragmentation by up to 34%.
Dispatches workloads via native eBPF hooks with zero context-switch overhead and real-time process monitoring.
Detects packet drops, synthesizes on-the-fly Ansible/sysctl remediations, and balances thermal loads dynamically.
Core modules currently under active engineering for enterprise on-premises HPC and hyperscale GPU clusters.
Ultra-low latency OS daemon bridging frontier reasoning LLMs with Linux eBPF telemetry, preserving stateful memory across hardware faults.
Seamlessly unifies Slurm HPC batch queues with modern Kubernetes pods, delivering continuous multi-tenant GPU packing.
Probes 400 Gbps InfiniBand Quantum-2 and NVSwitch interconnects in real-time, preempting all-reduce collective hangs.
Automatically generates, validates in sandbox, and canary-deploys minimal-diff Ansible playbooks and Terraform configs.
Embed autonomous agent infrastructure control directly into your Python pipelines with a single pip install azin-agent.
Completely offline on-premise architecture engineered for defense, semiconductor, and sovereign AI research labs.
Watch live autonomous agent sessions executing real-time cluster triage, GPU defragmentation, and zero-human remediation.
How a shared vision for automated HPC operations evolved from late-2025 concept discussions into an active engineering endeavor.
"The guiding motivation behind Azin: transforming cluster operations from stressful firefighting into an automated loop—seamlessly connecting job scheduling, anomaly detection, monitoring, and tuning."
Estimate annual engineering hours saved and idle compute costs recovered by deploying Azin across your cluster.
Answers to key security, integration, and operational questions from HPC infrastructure leads.
Yes. Azin Private Edition runs fully on-premises with localized lightweight inference runtimes on your master nodes. Zero telemetry leaves your secure network perimeter.
Azin does not replace your scheduler. It runs as a sidecar/daemon communicating via standard APIs and eBPF hooks, preserving your established job scripts and policies 100%.
Every synthesized IaC remediation is verified inside an isolated sandboxed dry-run before canary rollout. Organizations can enforce manual human-in-the-loop approvals anytime.
Via our automated Helm charts and RPM/Debian daemon packages, clusters can be onboarded in under 15 minutes with out-of-the-box Prometheus/Grafana integration.
We welcome enterprise cluster teams, research universities, and AI labs seeking private beta participation.
Receive access tokens for Azin Kernel v0.4 private builds and our comprehensive architecture whitepaper.
Inquire about custom HPC cluster deployments, on-premise PoCs, or technical keynotes.