01Services

AI infrastructure your platform team can operate.

Pipelines, registries, serving, evals, and observability built into the stack you already run. Not another silo.

Platform live
0-8wk
Train to serve
<0hr
Reproducible runs
0%
On-call ready
0/7
03What it is

The platform layer most teams build accidentally.

Training pipelines, feature stores, model registries, online serving, eval gates, and observability. We assemble it from open-source and your existing infrastructure, instead of buying yet another all-in-one platform.

  • Training pipelines (Kubeflow, Argo, Airflow, custom)
  • Model registry, versioned datasets, and reproducible training
  • Online and batch serving with autoscaling and cost dashboards
See evals & observability
04How we deliver

From discovery to production.

  1. 01

    Discover

    Audit your current AI infra, identify the gaps that block velocity, and pick the smallest set of changes that moves the needle.

  2. 02

    Build

    Stand up the missing layer on the tools you already run. We do not force a migration.

  3. 03

    Deploy

    Wire CI eval gates, monitoring, and on-call paths into your existing observability stack.

  4. 04

    Hand off

    Documented runbooks, training, and a knowledge transfer that lasts. Your team owns the platform.

Tired of one-off training scripts and Friday-night model deploys?

Book a 30-min consult
07Built for production

Your team owns it after we leave.

Every pipeline has a runbook. Every dashboard has an owner. Every release has an eval gate. We walk away when your platform team can take a model from notebook to production without us.

  • Runbooks and architecture docs for everything we build
  • Training and knowledge transfer until your team is autonomous
  • Open-source first, vendor lock-in avoided
See ML solutions
09FAQ

Common questions.

10Get started

Make AI deploys boring.

Free 30-minute consultation. We'll size the gap and the path to close it.

Schedule consultation