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Infrastructure-Agnostic Enterprise ML Platform — 3 Generations

Client name withheld · AI & Machine Learning

2 years
AI Infrastructure & MLOps
Platform & Cloud Engineering
Real-time & Industrial Data Platforms
Product Engineering

Platform generations

3

Engagement length

2 years

Deployment targets

AWS · GCP · on-prem

A global technology consultancy needed a reusable, production-grade ML platform that could be deployed across multiple client environments without being tied to a specific cloud vendor.

What changed

Before

Per client

Rearchitected for each engagement

After

Pipelines

Kubeflow

TensorFlow

Serving

Seldon

Monitoring

Prometheus

Grafana

Targets

AWS

GCP

On-premise

One platform definition that lands unchanged on three very different substrates — which is what made it reusable across clients.

What we built

The client needed an ML platform that could be adopted across multiple enterprise client engagements without rearchitecting for each. The platform had to cover the full ML lifecycle, be cloud-agnostic, and maintain enterprise-grade monitoring, CI/CD, and governance across all deployments.

Key Features

Infrastructure-agnostic, Spark-centric ETL with full CI/CD across dev, UAT, and production.

ML pipeline orchestration with Argo Workflows and Kubeflow for experiment and run management.

TensorFlow/Keras model serving via Seldon with canary deployment support.

Grafana, Prometheus, and GrayLog for end-to-end model performance and infrastructure monitoring.

mlflow for experiment tracking, model versioning, and registry management.

Docker and Kubernetes as the core deployment substrate enabling cloud-agnostic portability.

Three major platform generations delivered as the ML ecosystem matured.

Results

Reusable ML platform adopted across multiple enterprise client engagements.

3 major platform versions delivered across a 2-year engagement.

Deployment portability across AWS, GCP, and on-premise environments achieved.

Model serving latency and throughput monitored in production via Seldon + Prometheus.

Stack

Kubeflow
TensorFlow
Seldon
Grafana

Engagement: 2 years · AI Infrastructure & MLOps, Platform & Cloud Engineering, Real-time & Industrial Data Platforms, Product Engineering

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