Available for new projects

Ship LLMs to Production —
Without Burning the GPU Budget

GPU spend you can't explain. Models that work in notebooks but break at scale. RAG pipelines with no observability. We close the gap — vLLM, KServe, Kubernetes, and real cost visibility — for AI startups who need it in production, not forever in staging.

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vLLM KServe Kubernetes RAG LangChain GPU Infra Qdrant KEDA ArgoCD Terraform

The Problem

Sound Familiar?

If any of these keep you up at night, we should talk.

LLM works in notebooks. Breaks in production.

No model serving layer, no inference server, no GPU scheduling. Your data science team hands off a model. Your infra team has no idea what to do with it.

GPU bill has no attribution — you can't tell what's burning money

No per-tenant cost visibility, no scale-to-zero, idle GPU nodes running 24/7. You're paying for compute nobody is using.

RAG pipeline works in demos. Fails on real queries.

No observability, no trace logging, no way to know what your retrieval is actually returning. Every LLM call is a black box.

"It works at 5 req/s." Doesn't at 500.

No load testing, no horizontal scaling, no batching strategy. KV cache not configured. Your inference server wasn't built for production traffic.

What We Do

Our Services

Production-grade infrastructure, not "hello world" clusters. Every engagement is tailored to your stack.

AI Platform & MLOps

Most requested

LLM Inference Platform

  • ✓ vLLM or TGI on GPU Kubernetes (EKS/AKS)
  • ✓ KServe model endpoints with autoscaling
  • ✓ Langfuse observability + DCGM GPU metrics
Get a Quote →

RAG Pipeline Engineering

  • ✓ LangChain or LangGraph pipeline architecture
  • ✓ Qdrant vector store on Kubernetes
  • ✓ LiteLLM AI gateway + Langfuse trace logging
Get a Quote →
Free intro available

LLM Cost Audit

  • ✓ GPU utilization & idle waste analysis
  • ✓ Per-model/tenant cost attribution
  • ✓ Written action plan: top 3 savings levers
Get a Quote →
Aug 2 deadline

EU AI Act Compliance

  • ✓ Article 50 transparency obligation audit
  • ✓ AI-SBOM, model cards, audit trail setup
  • ✓ Kyverno/OPA policy set for AI Act controls
Get a Quote →

Infrastructure Foundation

GPU Kubernetes Setup

  • ✓ Production EKS/AKS with GPU node pools
  • ✓ KEDA scale-to-zero + DCGM monitoring
  • ✓ Zero-downtime migration with Helm + ArgoCD
Get a Quote →

FinOps for AI

  • ✓ OpenCost per-tenant GPU attribution
  • ✓ Spot GPU fleet + reserved capacity strategy
  • ✓ Scale-to-zero automation for idle workloads
Get a Quote →

CI/CD for ML

  • ✓ Model deployment pipelines (ArgoCD + Argo Workflows)
  • ✓ Automated testing + security scanning
  • ✓ GitOps model versioning & rollback
Get a Quote →

Infrastructure as Code

  • ✓ Terraform / Pulumi / CloudFormation
  • ✓ Multi-cloud IaC strategy & modules
  • ✓ State management & drift detection
Get a Quote →

Need an Embedded AI Platform Engineer?

Dedicated retainer — LLM infrastructure maintenance, model deployment support, incident response & on-call. Starting at $4,000/month.

Discuss Retainer

About

Meet the AI Platform Engineer Behind TheStartupOps

Vikram Singh — Founder, TheStartupOps

Vikram Singh

Founder & AI Platform Engineer

15+ years | vLLM · KServe · GPU Kubernetes · RAG · FinOps

View LinkedIn Profile →

I've spent 15+ years building and scaling infrastructure for enterprises and startups. For the past two years, that means one thing: getting LLM models out of notebooks and into production — with real serving infrastructure, real cost visibility, and real uptime.

vLLM and KServe on Kubernetes. RAG pipelines with Langfuse observability. GPU autoscaling that scales down to zero when idle. CKA and CKS certified — so the security is built in, not bolted on.

15+

Years Experience

$48K

GPU Costs Cut

0

Downtime Migrations

Tech Stack

vLLM

KServe

LangChain

Qdrant

LiteLLM

Langfuse

MLflow

Kubeflow

Kubernetes

EKS

AKS

Terraform

ArgoCD

Helm

KEDA

OpenCost

Prometheus

Grafana

Docker

GitHub Actions

Python

Ansible

GitLab CI

ELK Stack

Track Record

Real Results

What happens when AI startups get their infrastructure right.

$48K

GPU Inference Costs Cut Per Year

Spot GPU pools, KEDA scale-to-zero, OpenCost per-tenant attribution. 30% Azure spend reduction in 60 days.

AI Fintech — Series B
15

Microservices Migrated to EKS

6 weeks, zero downtime. Full Terraform IaC, Helm charts, and ArgoCD GitOps pipeline.

Platform Infra — Series B
40%

Cloud Bill Reduced

Right-sized inference clusters, spot fleet, reserved GPU capacity. Saving $8K/month.

SaaS AI — Series A
8 min

Model Deploy Time (was 2 hours)

ArgoCD GitOps pipeline with automated testing. 50+ model deploys/day with zero manual steps.

AI Platform — Seed Stage

Writing

Case Studies

View all →
FinOps for AI Azure AKS KEDA vLLM

How We Cut $48K/Year in GPU Inference Costs on Azure AKS

No attribution, no scale-to-zero, idle GPU nodes running 24/7. 60 days later: 30% spend reduction, full per-model cost visibility, batch workloads on spot with KEDA.

Read case study →
$48K saved/yr
LLM Inference KServe Coming soon

Production vLLM + KServe on EKS: Zero to 800ms p95

Series A AI startup. Mistral 7B. KServe InferenceService, DCGM monitoring, Langfuse observability. End-to-end build from scratch.

Publishing soon

Process

How It Works

From first call to production-ready in weeks, not months.

1

Discovery Call

Free 15-min call to understand your stack and goals.

2

Audit & Proposal

We assess your infra and deliver scope, timeline & quote.

3

Build & Ship

We implement — inference platform, RAG pipeline, IaC, CI/CD, GPU monitoring — with weekly async updates.

4

Handoff & Support

Full docs, team training & optional ongoing retainer.

FAQ

Common Questions

Get a FREE LLM Cost Audit

We'll review your current LLM infrastructure: GPU utilization, inference costs, RAG pipeline observability, and Kubernetes serving setup — and give you a written audit with the top 3 cost and reliability improvements. No commitment.

Currently taking 3 new clients per month

Book Your Free 15-Min Call

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Contact

Let's Talk AI Infrastructure

Have a question or want to discuss a project? Send a message and we'll reply within 24 hours.

hello@thestartupops.com
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Pro tip: Want a faster response? Book a free call — you'll get a time slot within 24 hours.

We reply within 24 hours. No spam, ever.