The dream of deploying transformative AI applications is powerful. Yet, many brilliant AI teams find themselves stuck in the “AI Platform Chasm”—the vast, complex gap between a working model and a secure, scalable, production-ready system. Building this Cloud-Native AI Infrastructure from scratch is a daunting task, often taking months, if not years, and burning through valuable resources.
But what if there was a way to Accelerate AI to Production? This is where AI Infrastructure Services come in. This ultimate guide will walk you through how Drizzle Systems delivers production-ready AI infrastructure, our core services, benefits, and transparent pricing.
What is AI Infrastructure as a Service?
AI Infrastructure Services, like those offered by Drizzle Systems, are designed to drastically reduce the time, cost, and complexity of building and deploying robust AI and Machine Learning infrastructure. Instead of starting from zero, you leverage pre-built, battle-tested components, deep automation, and expert guidance.
Think of it as getting the keys to a high-performance race car chassis, already equipped with a powerful engine and telemetry (our MLOps as a Service approach), rather than trying to design and weld every piece yourself. This allows your team to focus on customizing the car for your specific race (your unique AI models and applications) and getting to the finish line faster.
The Drizzle Systems Difference: Benefits of Our AI Infrastructure Services
Choosing Drizzle Systems means choosing a partner dedicated to your success and independence. Our core benefits include:
- Unmatched Speed to Production: We deliver a Production-Ready AI Infrastructure in weeks, not months or years. This is achieved through our battle-tested blueprints and expert automation.
- You Own Your AI Stack, 100%: Unlike proprietary platforms or traditional consultancies that create lock-in, we deliver all the Infrastructure as Code. You have full control and ownership.
- Production-Grade from Day One: Security, scalability, and observability aren’t afterthoughts; they are built into the foundation of every infrastructure we deliver.
- Significant Cost Savings: Avoid the massive expense of hiring a large, specialized MLOps team or the unpredictable costs of lengthy DIY projects.
- Expertise On Demand: Gain immediate access to seasoned MLOps, SRE, and Cloud-Native professionals who understand how to serve LLMs with GPUs efficiently and build scalable LLM apps with Kubernetes.
The Core Pillars Of Our Solutions
Every Drizzle platform is built on foundational pillars that ensure it is modern, scalable, secure, and ready for production from day one.
Unified Automation with IaC & GitOps We use a unified approach to automation. Your core infrastructure is built with Terraform (IaC), and your applications are deployed with Argo CD (GitOps), creating a single, auditable system for managing your entire platform.
- Infrastructure as Code using Terraform
- Declarative GitOps deployments with Argo CD
- A single source of truth for your entire stack
Optimized for LLM Serving Utilize state-of-the-art inference engines like the vLLM Production Stack, AIBrix or NVIDIA Dynamo to create a tailored GenAI inference infrastructure on Kubernetes.
- LLM inference and serving with vLLM
- Production implementation with KServe, vLLM Prod Stack and AIBrix
- Essential building blocks to construct scalable GenAI inference infrastructure
- High-throughput, low-latency inference
- Cost effective cloud deployment
Full-Stack Observability Monitor everything from GPU utilization to token costs with our integrated O11y Stack, built on Prometheus, Grafana, Langfuse and OpenTelemetry.
- Real-time metrics and tracing with Prometheus and Langfuse
- Pre-configured Grafana dashboards
- Monitor GPU usage & LLM token costs
- Pre-build LLM alerting with Alert Manager
Our AI Infrastructure Services
Our solutions are built on three core principles: unified automation for speed, a secure and scalable inference engine for performance, and complete observability for control.
Infrastructure Engineering (The Foundation)
We build your cloud-native GPU-based infrastructure platform foundation on AWS, GCP, or Azure, or On-Prem using Infrastructure as Code, GitOps and CI/CD.
- Run anywhere: AWS, Azure, GCP, on-premises, or hybrid environments with consistent behavior.
- GPU-powered Kubernetes clusters in secure VPC environments.
- Serverless Inference Workloads - Automatic scaling including scale-to-zero on both CPU and GPU
- Service Mesh
- Canary rollouts and A/B testing
AI/LLM Engineering (The Engine)
Deploy the engine for your AI/LLM applications. You’ll be provided with a robust, production-grade Inference Platform.
- OpenAI-Compatible APIs
- Serverless Inference Workloads and Dynamic custom scaling
- Unified AI/LLM Gateway with Envoy AI Gateway Integration
- Multi-frameworks Support (Hugging Face, vLLM, AIBrix, and custom models)
- KV Cache Offloading and Distributed LLM serving
- Local Model Cache for faster startup
- High Scalability and Density using LLM Mesh
AI/LLM Infrastructure Observability (The Cockpit)
You can’t optimize what you can’t see. We deploy a complete, AI-native observability stack so you can monitor everything from GPU utilization to token costs from day one.
- Real-time monitoring with Prometheus and Grafana
- Agents and LLM tracing and analytics with Langfuse
- Track performance, cost, and usage metrics
- Pre-built dashboards and alerts.
Professional Services & Team Enablement
Accelerate your AI transformation with expert guidance and comprehensive support. From strategic advisory to hands-on training, we ensure your team masters the technology and your infrastructure scales with confidence.
Platform Advisory
Platform Advisory gives you a direct line to our experts, it’s like having a fractional Cloud AI CTO in your Slack.
- Direct line to senior engineers & architects.
- Tailored strategic guidance aligned with your requirements and business objectives.
- Guidance on migrations, architecture, and compliance.
- Avoid costly missteps and accelerate decisions.
Team Enablement & Training
Empower your team with the knowledge and skills to maximize the value of your AI infrastructure.
- Role-Based Training Programs: Tailored workshops for DevOps, MLOps, and AgentOps teams.
- Deep-Dive Technology Sessions: Hands-on training with Terraform, Kubernetes, KServe, Terraform, Prometheus, Grafana, vLLM, AI Gateway, and more.
- Custom Documentation: Comprehensive runbooks, playbooks, and operational guides.
- Knowledge Transfer Sessions: Structured sessions to ensure your team can independently manage the infrastructure.
Legacy Platform Migration
Move workloads from brittle or costly setups to your new cloud-native platform.
- Assessment, phased migration plan, and rollback strategy.
- Data and model compatibility validation.
- Execution by the team that built the core stack.
Custom Agent ystems Deployment
Deploy your custom AI client applications, intelligent agents, or MCP servers with ease. Our team ensures efficient and secure deployment on your built-in Drizzle Systems Stack, leveraging optimized LLMs and GPU-powered Kubernetes for peak performance.
- Ship AI apps, intelligent agents, or MCP servers with repeatable GitOps.
- From single apps to complex multi-agent systems.
- Full GitOps deployment using Helm and ArgoCD.
- Support for single apps to complex microservice architectures.
- Secure connectivity and integration with your platform’s AI resources and Models.
You can explore our unique services in more detail on our Drizzle Systems Services Page
The Core Technologies We Master: Our Building Blocks
A Drizzle Systems infrastructure isn’t a black box. It’s built by expertly integrating a curated stack of best-in-class, open-source, and cloud-native technologies. This approach ensures your infrastructure is powerful, transparent, flexible, and future-proof. Here are some of the key components:
- Infrastructure as Code (Terraform): Your entire cloud and Kubernetes infrastructure is defined and managed using Terraform. This guarantees automation, repeatability, and gives you full ownership of the code.
- Kubernetes (EKS, GKE, AKS): We deploy your AI workloads on leading managed Kubernetes services from AWS, GCP, or Azure, providing a scalable and resilient foundation.
- vLLM Production Stack: For state-of-the-art LLM inference performance, we implement the full vLLM stack, including Ray Serve, to maximize throughput and minimize GPU costs.
- KServe: Standardized Distributed Generative and Predictive AI Inference Platform for Scalable, Multi-Framework Deployment on Kubernetes. (Read more in our new complete KServe guide : https://drizzle.systems/blog/kserve-ultimate-guide/)
- AIBrix Stack: Designed for enterprise teams seeking highly customizable and modular inference solutions. AIBrix offers a cloud-native infrastructure optimized for deploying, managing, and scaling large language model (LLM) inference, with fine-grained control and enterprise-grade features tailored to your specific needs.
- Argo CD & GitOps Workflows: We implement modern GitOps practices using Argo CD for automated, auditable, and secure application deployments to your Kubernetes cluster.
- The O11y Stack (Prometheus, Grafana, OpenTelemetry): Gain deep insights into your infrastructure’s performance, costs, and reliability with our integrated observability solution.
- Vector Databases (e.g., Qdrant): We deploy and manage production-ready vector databases, essential for modern RAG applications and semantic search.
You can explore these and other technologies we leverage in more detail on our Technology Stack page
Why Choose Drizzle Systems for Your AI Infrastructure?
Drizzle AI Systems is more than just a service provider; we are your dedicated infrastructure partner.
- Open & Modern Stack: We exclusively use best-in-class, open-source, and cloud-native technologies.
- True Ownership: Our “You Own It 100%” philosophy is a core tenet.
- Pragmatic Speed: Our blueprint-driven approach delivers velocity without sacrificing quality.
- Predictable Outcomes: Our fixed-price project model ensures no surprises.
- LLM Specialization: We have deep expertise in helping teams build scalable LLM apps with Kubernetes and efficiently serve LLMs with GPUs.
- Partnership Approach: We don’t just deploy and disappear. We’re your long-term partners in AI infrastructure success, providing expert support, training, and strategic guidance.
- Guaranteed Results with Transparency: Experience predictable outcomes delivered on time and within budget through our streamlined process. Benefit from direct team communication, zero hidden fees, and no long-term commitments—just reliable, straightforward service.
Ready to Make it 10x Easier to Production-Grade AI Infrastructure?
Stop struggling with complex AI infrastructure decisions. Our experts deliver production-ready, scalable AI systems tailored to your business needs. Get the benefits of enterprise-grade infrastructure without the months-long implementation headaches or vendor lock-in concerns.
