AI Infrastructure

Intelligence requires
Industrial Power.

We engineer the high-performance compute clusters, inference engines, and MLOps backbones that allow you to train, fine-tune, and serve models at scale.

Industrial MLOps

A laptop is not a production environment. We build "Golden Paths" that take models from Jupyter Notebooks to Kubernetes endpoints automatically.

By implementing Feature Stores, Model Registries, and CI/CD for Machine Learning (CML), we standardize the mess of experimental code into reproducible, versioned software artifacts.

Automated Retraining Pipelines
Feature Store Implementation
Model Lineage & Versioning
Experiment Tracking (MLflow)

High-Performant Inference

Latency is revenue. We optimize inference servers using NVIDIA Triton and vLLM to squeeze every drop of performance out of your hardware.

Our architectures support dynamic batching, model quantization (AWQ/GPTQ), and specualtive decoding, allowing you to serve 70B parameter models with sub-20ms latency.

Sub-20ms Token Latency
Dynamic Batching
Speculative Decoding
Multi-Model Endpoints

Compute Orchestration

GPUs are expensive assets. We ensure you aren't paying for idle silicon. We implement Kubernetes-based GPU slicing (MIG) and fractional scheduling.

Our "FinOps for AI" modules automatically scale clusters down to zero when idle and burst to spot instances during training runs, optimizing your Total Cost of Ownership.

GPU Slicing (MIG)
Spot Instance Orchestration
Multi-Cloud Bursting
Cluster Auto-Scaling

The Platform Stack

We don't just use tools; we architect cohesive platforms.

Inference Server

Standardized on NVIDIA Triton and vLLM for universal model support (TensorFlow, PyTorch, ONNX).

Feature Store

Centralized feature definitions using Feast or Tecton to prevent training-serving skew.

Observability

Deep monitoring of GPU saturation, memory bandwidth, and model drift using Prometheus stack.

Governance is not Optional

We build platforms that satisfy the most paranoid sec-ops teams.

  • Role-Based Access Control (RBAC) Notebooks
  • Audit Logs for Every Inference
  • VPC Service Controls
  • Container Scanning & Signing

Hybrid & Air-Gapped

Whether you run on AWS, Azure, or a private data center in a bunker, our Kubernetes-based architectures are portable and sovereign.

Built by Systems Engineers

Scale Proven

We've architected clusters that train models on petabytes of data without crashing.

Resilient

Self-healing infrastructure that automatically restarts failed nodes and reroutes traffic.

Vendor Neutral

We don't lock you into a single cloud. We build on open standards like Kubernetes and Ray.

Ready to scale?

Stop fighting with CUDA drivers. Start deploying intelligence.

Assess Your Infrastructure