Our Accelerator Services
We offer a flexible range of services to get your AI platform to production faster. From a DIY blueprint for expert teams to a full-service launchpad, our goal is to bridge the AI Platform Chasm and deliver a Production-Ready AI Platform that accelerates your innovation.
The Drizzle:AI Blueprint
For teams with strong internal expertise, our Blueprint provides the complete, battle-tested Infrastructure as Code and documentation for our modern AI platform. It's the ultimate head start, saving you months of research and development.
- Get our battle-tested AI platform code for a seamless start.
- Comprehensive, step-by-step implementation documentation.
- A 2-hour architectural kick-off session with our expert founders.
- Full customization flexibility to suit your needs.
- No long-term commitments—retain full control.
- Optional expert support available when you need it.
The Drizzle:AI Launchpad
Our flagship white-glove service, offering MLOps as a Service for a full, hands-on implementation of your Production-Ready AI Platform. Our expert team handles everything, delivering a complete solution in weeks that you own 100%.
- Includes everything in the Blueprint package.
- A secure, cloud-native infrastructure foundation (Phase I).
- A powerful AI/LLMOps engine using JARK, vLLM, or AIBrix open-source stacks on Kubernetes (Phase II)
- A complete observability cockpit for monitoring and costs (Phase III).
- Full hand-off, documentation, and 100% code ownership (Phase IV).
- Money-back Guarantee
- 2 to 4 Week Implementation Time
- Optional expert support available when you need it.
Add-On: AI Application & MCP Servers 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:AI platform, leveraging optimized LLMs and GPU-powered Kubernetes for peak performance.
- 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.
Add-On: Co-Pilot Support Packages
Ensure the ongoing success and reliability of your platform with our dedicated support retainers, giving you direct access to our expert team.
- Two tiers available: Standard & Premium.
- Priority access for platform-related questions & troubleshooting.
- Proactive guidance and best-practice advice.
Add-On: DevOps & MLOPS Training
Empower your team with custom workshops to master the powerful cloud-native and AI tools used in your Drizzle platform, such as Terraform, Kubernetes, ArgoCD, vLLM, AIBrix, Ray, and your chosen cloud provider (AWS, GCP, Azure).
- Hands-on training for DevOps and LLMOps
- Deep dives into vLLM, Ray, NVIDIA Dynamo, AIBrix and the Observability stack.
- Customized content based on your team's specific needs.
Add-On: Legacy Platform Migration
Modernize your existing AI/ML workloads by migrating them from legacy systems to your new, powerful Drizzle cloud-native platform.
- Comprehensive assessment of your current legacy setup.
- Strategic planning for a phased and secure migration.
- Hands-on execution of the migration process by our experts.
The Drizzle:AI Launchpad: Our 4-Phase Process
Our Drizzle:AI Launchpad service is a comprehensive, four-phase engagement designed to take you from concept to a fully operational, production-ready AI platform in weeks. Each phase builds upon the last, ensuring a secure, scalable, and observable solution that you own entirely. Explore the journey below.
Infrastructure Engineering (The Foundation)
We build your cloud-native GPU-based infrastructure platform foundation on AWS, GCP, or Azure using Terraform Infrastructure as Code, GitOps and CI/CD.
- Fully Managed Kubernetes Cluster, powered by GPU Nodes, Deployed into a secure VPC
- We support natively AWS, GCP and Azure.
- Cluster Autoscaling Implemented by Design.
- Terraform Infrastructure as Code.
- Rquired cloud infrastructure resources such as networking layer, databases, storage, messaging and queuing,…etc
AI/LLMOps Engineering (The Engine)
Deploy the engine for your AI applications. You’ll will be provided with a powerful options: the versatile JRAK Stack, the high-throughput vLLM Production Stack, high-scalable AIBrix, or NVIDIA Dynamo Platform for optimized LLM deployment, to construct scalable enterprise-grade GenAI inference infrastructure on Kubernetes.
- The JARK Stack: Jupyter, Argo, and Ray on your Kubernetes cluster. For teams that need a versatile environments for both developing and serving scalable AI/ML apps.
- The vLLM Production Stack: For teams focused on high-throughput and low-latency LLM inference. This provides a blazing-fast, cost-effective serving solution right out of the box.
- AIBrix: Designed for enterprise teams seeking highly customizable and modular inference solutions. AIBrix offers a cloud-native platform optimized for deploying, managing, and scaling large language model (LLM) inference, with fine-grained control and enterprise-grade features tailored to your specific needs.
- NVIDIA Dynamo: High-performance, low-latency inference platform designed to serve all AI models. For teams looking for the fastest path to inference with (NVIDIA) GPU acceleration, industry-standard APIs, and enterprise-grade security for building copilots, chatbots, and AI assistants.
AI Model Deployment & Serving (The Model)
With the platform and serving engine (e.g., using vLLM or AIBrix's building blocks) in place, the next step is to deploy your chosen AI model(s). We help you serve any compatible model, whether it's from Hugging Face or one you've developed in-house.
- Deploy open-source models directly from Hugging Face or bring your own custom-developed models.
- Our platform is designed to support multi-model serving, allowing you to deploy and manage several different models simultaneously.
AI/LLM Platform Observability (The Cockpit)
You can't fly blind. We'll give you the tools to monitor everything under the hood.
- We deploy a complete, out-of-the-box observability solution based on OpenTelemetry Prometheus and Grafana. This includes gathering telemetry in the form of metrics, traces and logs coming from your AI/LLM Platform and the underlying infrastructure.
- You get pre-built dashboards to monitor critical metrics like GPU utilization, Time for First Token (TFFT), Time for Output Token (TFOT), Prompt/Generation Tokens per Second, request throughput and overall cloud costs.
Your Modern, Cloud-Native, Production-Ready AI Platform, Accelerated
We deliver production-ready AI Platform, backed by our acclerator support in weeks, not months