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Cloud & AI

AI/ML Workloads on Kubernetes

Deploy, orchestrate, and scale AI/ML models with specialized Kubernetes infrastructure for high performance and cost efficiency.

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Our core capabilities

Our AI/ML Kubernetes Solutions

AI/ML Orchestration

Kubeflow, KServe & AI Model Serving

Automate ML workflows with scalable orchestration, optimized model serving, and seamless multi-cloud deployment.

Key benefits

  • Deploy AI models 60% faster for a competitive edge
  • Cut costs with automated scaling & efficiency
  • Improve model reliability & uptime

For tech leads

  • Automate ML workflows with Kubeflow
  • Serve models in real-time with KServe
  • Multi-cloud & hybrid Kubernetes support

MLOps Automation

Continuous Training & Model Monitoring

Enhance AI performance with automated retraining, real-time monitoring, and robust security compliance.

Key benefits

  • Reduce AI maintenance by 40% with automation
  • Ensure compliance with built-in security controls
  • Improve model accuracy & reduce AI bias

For tech leads

  • Continuous training & validation workflows
  • Secure API gateways for AI pipelines
  • Real-time AI performance monitoring

LLM & Data Pipelines

Scalable AI Data Workflows

Streamline AI pipelines with event-driven processing, cost-efficient LLM fine-tuning, and adaptive inference.

Key benefits

  • Lower AI infra costs with optimized LLM execution
  • Streamline large-scale AI data pipelines
  • Boost LLM performance while reducing latency

For tech leads

  • Scalable ETL & event-driven AI pipelines
  • Optimize LLM fine-tuning & inference
  • Automate monitoring & retraining

For product & tech leaders

Why Choose Our AI/ML Solutions?

For Decision Makers

  • Reduce operational costs with auto-scaling ML workloads.
  • Improve time to market with automated ML pipelines.
  • Increase AI model reliability with continuous monitoring.

For Tech Leads

  • Optimized Kubernetes clusters for ML training & inference.
  • Support for Kubeflow, KServe, TensorFlow, PyTorch, ONNX.
  • Secure, scalable, and fully managed MLOps pipeline.

What this covers

A person approves every action before it runs

AI governance

Aokumo AI helps provision the cluster you already operate

On-prem AI

The system carries the steps, the exceptions, and the record

Business workflows

Need AI/ML solutions tailored to your needs?

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How it works

Our AI pipeline in four steps.

01

AI Model Training

02

ML Orchestration

03

Continuous Monitoring

04

Optimization

Our AI/ML Kubernetes solution automates the entire lifecycle, from training to deployment.

Technical foundations

Tech Stack Overview

Kubeflow

ML Orchestration & Pipelines

Automates ML workflows on Kubernetes

KServe

AI Model Deployment & Inference

Serverless inference on Kubernetes

Gloo AI Gateway

LLM Traffic Management & Security

AI-specific API gateway for Kubernetes

Terraform

Infrastructure as Code

Manages Kubernetes clusters across clouds

ArgoCD

CI/CD for AI

GitOps-based deployments on Kubernetes

Multi-Cloud AI

Multi-Cloud AI Infrastructure

Deploy AI workloads across AWS, GCP & Azure

FAQ

Frequently Asked Questions

We support TensorFlow, PyTorch, Scikit-learn, ONNX, Hugging Face, and more.

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Optimize Your AI/ML Workloads on Kubernetes

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