Deploy Your Own Private ChatGPT on AWS in 30 Minutes

What if you could deploy a fully private ChatGPT alternative — on your own AWS infrastructure, with your own data sovereignty rules — in 30 minutes?

No third party between your users and your models. No per-seat fees. Two Terraform commands, once you have a domain, a certificate and the model access you want.

Here's how.

The Stack¶

stdapi.ai sits between Open WebUI and AWS Bedrock, translating OpenAI API calls into native AWS requests. Standard SDKs connect on the base URL alone — Open WebUI, n8n, VS Code AI assistants, custom apps.

User → Open WebUI → stdapi.ai → AWS Bedrock → Claude Opus 4.6, DeepSeek, Kimi, Mistral…
                                             → AWS Polly (text-to-speech)
                                             → AWS Transcribe (speech-to-text)

What You Get¶

• 100+ AI models — Claude, DeepSeek, Kimi, Mistral, Cohere, Stability AI, and more
• Full multi-modal support — Chat, voice input/output, image generation/editing, document RAG
• Multi-region access — Configure multiple AWS regions for the widest model selection and availability
• Pay-per-use — No ChatGPT subscriptions, no per-seat fees. You pay only for actual AWS Bedrock usage
• Production-ready infrastructure — ECS Fargate with auto-scaling, Aurora PostgreSQL + pgvector for RAG, ElastiCache Valkey, dedicated VPC, HTTPS with ALB

Data Sovereignty & Compliance¶

This is where it gets interesting for regulated industries:

• Region allow-lists — Pin inference to the AWS regions you approve. Whether that satisfies a given obligation is a judgement for you and your advisers; the gateway supplies the control, not the conclusion
• No data shared with model providers — AWS Bedrock does not share your inference data with model providers
• No training on your data — Your prompts and responses are never used for model training
• Two models are an exception worth knowing — Claude Fable 5 and Claude Fable 5.1 require your account to allow AWS's own human review of retained traffic, within the AWS boundary and for up to 30 days; the compliance guide covers every retention mode in full
• No third party in the request path — traffic goes from your application to your own deployment to AWS
• Dedicated VPC — Isolated network for your AI workloads

Whether you need to keep data in the EU, in specific US regions, or within national boundaries for government requirements — you configure the allowed regions and stdapi.ai enforces it.

Deploy in 30 Minutes¶

git clone https://github.com/stdapi-ai/samples.git
cd samples/getting_started_openwebui/terraform

# ⚙️ Customize your settings (regions, models, scaling…)
# → Check the full documentation in the repo to tailor the deployment to your needs

terraform init && terraform apply

That's it.

What Terraform deploys for you:¶

• Open WebUI on ECS Fargate with auto-scaling
• stdapi.ai as the OpenAI-compatible AI gateway
• Aurora PostgreSQL with pgvector extension for RAG
• ElastiCache Valkey for caching
• Dedicated, isolated VPC with HTTPS via ALB
• All environment variables pre-configured and ready to go

How stdapi.ai Works Under the Hood¶

stdapi.ai is more than a simple proxy. It's an AI gateway purpose-built for AWS that:

• Translates the OpenAI API — Chat completions, responses, conversations, embeddings, images (generation/editing/variations), audio (speech/transcription/translation), batches, vector stores, realtime speech, and model listing (as of v1.17.0, September 2026)
• Speaks other dialects on the same deployment — Anthropic, Cohere and Ollama clients each connect on their own route prefix
• Handles multi-region routing — Automatically selects the best region and inference profile for each model
• Exposes advanced Bedrock features — Prompt caching, reasoning modes (extended thinking), guardrails, service tiers, and model-specific parameters
• Integrates native AWS AI services — Amazon Polly for TTS, Amazon Transcribe for STT with speaker diarization, Amazon Translate

Your existing OpenAI-powered tools work without modification. Change the base URL, and you're on AWS.

Who Is This For?¶

• Teams that want a private ChatGPT with full data control
• Regulated industries (finance, healthcare, government) that need data residency guarantees
• Companies tired of paying per-seat ChatGPT subscriptions when usage varies wildly
• Developers who want to use the OpenAI ecosystem on AWS infrastructure
• Ops engineers who want production-grade AI infrastructure as code

Get Started¶

📦 Deployment repo: github.com/stdapi-ai/samples

📖 Documentation: stdapi.ai

📩 Need help? We can help you deploy and customize this solution for your needs. Reach out to us.

Two Terraform commands, and a private ChatGPT running in your own AWS account.