Infrastructure for AI
Run production-grade AI safely, efficiently, and at scale in your infrastructure, under your control.
GPU/TPU orchestration
With Kubernetes + Ray + vLLM/TensorRT-LLM
Monitoring, tracing, and evaluation
Via Langfuse + Prometheus + Grafana
Model serving pipelines
With low-latency inference and versioning
MLOps frameworks
For continuous delivery and governance
Engineering the layer where intelligence runs.
We design, deploy, and operate on-premise or cloud-native AI infrastructures optimized for LLMs, multimodal models, and agent systems, secure, compliant, and performance-tuned for enterprise workloads.
Designing AI that holds in production
From experimental stacks to resilient systems.
Production-First Infrastructure Design
Cloud-native or on-prem stacks architected for performance, isolation, and cost control, not demos.
Compute-Aware Orchestration
GPU/TPU workloads orchestrated with Kubernetes, Ray, and optimized runtimes like vLLM or TensorRT-LLM for predictable latency at scale.
Observable Intelligence
End-to-end monitoring, tracing, and evaluation pipelines using Langfuse, Prometheus, and Grafana, so model behavior is measurable, not assumed.