Services
MLOps & AI Infrastructure
Production-grade infrastructure for ML and LLM workloads: training pipelines, GPU orchestration, model registries, evaluation harnesses, and continuous deployment for models.
Ship Models with Confidence
We make ML and LLM systems boring in the best way — repeatable, observable, and safe to roll out.
GPU Orchestration
Ray, Modal, RunPod, on-prem
Continuous Delivery
Canary & shadow deploys
LLM Observability
Traces, evals, drift alerts
Safe by Default
Guardrails & PII redaction
10x
Faster Iteration
From notebook to production
What You Get
A platform that turns ML experiments into reliable products.
Training pipelines with reproducible artifacts
Model registry with versioning & lineage
GPU orchestration with Ray / Modal
Online & batch model serving infrastructure
Continuous evaluation & regression tests
LLM observability with Langfuse / Helicone
Feature store & data versioning
Canary rollouts and shadow deployments
PII redaction & governance controls
Cost & latency dashboards
Tech Stack
Tooling for serious ML operators.
MLflow
Weights & Biases
Ray
Modal
Triton
BentoML
KServe
Langfuse
Feast
DVC
Airflow
Kubeflow
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