AWS Marketplace — Self-Hosted AI Ecosystem
Self-Hosted AI for the Enterprise
Deploy a private, fully integrated AI ecosystem in your own AWS account — Ollama, LibreChat, degoog, and n8n pre-wired in a production-ready CloudFormation deployment. Your data, your models, your infrastructure — with no external data egress.
Available on AWS Marketplace
The Self-Hosted AI Integrated Sandbox is listed on AWS Marketplace. Professional delivery by Cloud Optimization Solutions — founded 2024 — deploys the complete stack into your AWS environment so your team can begin leveraging private, self-hosted AI capabilities right away.
What you get
Four Integrated Open Source Components
The delivered CloudFormation stack provisions and configures everything so your team can start running local LLM workloads immediately — all components already wired together and secured behind your own VPC. Typical applications include document processing and summarization, internal knowledge retrieval, research augmentation with web scraping, and repeatable AI-powered business workflows.
Ollama Server
Run large language models locally on GPU-powered EC2 instances within your account. Choose and manage the models that fit your use case without relying on third-party API providers.
LibreChat
A web-enabled chat interface that lets your team interact with your locally hosted LLMs — extensible to a websearch MCP (Model Context Protocol) so your AI can incorporate live web search results into its responses.
degoog
A web search and scraping agent that retrieves and processes external information without routing queries through major search engine APIs — giving you more control over how web data is gathered.
n8n (Community Edition)
A powerful workflow automation tool that connects to your local Ollama server and other data sources. Build structured workflows that retrieve data, process it through your LLM, and deliver results — without writing custom code.
How It Fits Together
In your AWS account
AWS Resources Provisioned
One-step deployment via CloudFormation provisions a production-ready environment — and because everything runs in your AWS account, you retain full ownership of all data processed by the LLM. Queries, responses, and workflow data remain within your environment.
EC2 Instances
Both CPU and GPU instances to power the AI inference and application layers.
Application Load Balancer
Routes traffic to the appropriate services and provides a single entry point.
NAT Gateways
Enable outbound internet access for components that require it while keeping your infrastructure private.
Security Groups
Network-level access controls that restrict traffic between components and from external sources.
Why self-hosted matters
Private AI, Fully Under Your Control
Data Sovereignty
Your prompts, documents, and AI outputs never leave your AWS account — no third-party API calls, no vendor retention policies.
No Per-Query API Costs
Run unlimited queries against your local models without usage-based fees to third-party AI providers.
Full Customization
Choose which LLM models to deploy and configure workflows tailored to your specific business needs.
Integrated Toolchain
Four complementary open source tools working together out of the box — reducing integration effort and eliminating vendor lock-in.
The process
Four Phases to Self-Hosted AI in Production
Assessment & Requirements
We audit your data sensitivity, workload profiles, and existing infrastructure readiness — compute, storage, networking, and security posture. Each candidate workload is classified by sensitivity and latency requirements, producing a self-host versus API decision matrix and a defensible total cost of ownership model for your leadership.
Architecture & Model Selection
We design the deployment topology — GPU sizing, serving architecture, vector store, and network isolation — and run structured evaluations of open-weight models against your representative data. The output is a reference architecture with security controls engineered in, plus a ranked model selection backed by documented evaluation results.
Deployment & Integration
Our engineers deliver the production-ready CloudFormation stack — Ollama, LibreChat, degoog, and n8n provisioned and pre-wired in your account. We implement access controls, request logging, and guardrails from day one, then validate with load, failover, and security testing before any production traffic lands.
Operations & Optimization
Post-launch, we operate and continuously tune the platform — monitoring utilization, latency, and model drift; running fine-tuning and evaluation cycles; and planning capacity ahead of demand. As open-weight models improve, we manage upgrade paths and re-evaluations so your self-hosted capability compounds instead of stagnating.
Measurable outcomes
What Self-Hosted AI Delivers
Ready to Deploy Your Private AI Stack?
Cloud Optimization Solutions will work with you to deploy the complete Self-Hosted AI Ecosystem into your AWS environment. Start with a no-obligation discovery call — AWS infrastructure costs for provisioned resources are incurred separately in your account.