Use Case #97 — Private Infrastructure

Deploy a Private AI Agent App on Your Own Infrastructure

Ship production-grade AI agents that run entirely within your own servers, VMs, or Kubernetes clusters. Full data sovereignty, zero cloud lock-in, and a working deployment in under 10 minutes.

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Trigger
API call, schedule, or internal event
Architect Agent
Runs entirely on your infrastructure
Live — Private Mode
Action
Internal APIs, databases, tools — all on-prem
Kubernetes Docker AWS VPC

Key Statistics

<10m
From config to live deployment
100%
Data stays on your infrastructure
70%
Lower operational cost vs. managed AI SaaS
0
External cloud dependencies required
Why It Matters

Your Data. Your Compute. Your Rules.

Regulated industries, security-conscious enterprises, and sovereign-data mandates cannot afford to route sensitive workloads through third-party AI clouds. Architect enables you to deploy fully functional AI agent applications inside your own perimeter — without sacrificing developer velocity, capability, or compliance posture.

100%
Data sovereignty guaranteed
<10m
Setup time on your own infra
70%
Cost reduction vs. managed AI SaaS
Integrations

Runs Where You Already Operate

Architect connects to your existing infrastructure stack — cloud, on-premise, or hybrid — without requiring data to leave your environment.

Kubernetes
Docker
AWS Private VPC
Azure Private Link
GCP VPC
PostgreSQL
Ollama (Local LLM)
HashiCorp Vault
Prometheus
Platform Capabilities

Built for Private, Secure Deployments

Fully Self-Hosted Architecture
Deploy the entire Architect runtime — agent engine, orchestration layer, and UI — on your own VMs or Kubernetes cluster. Nothing phones home. No telemetry leaves your perimeter.
Bring Your Own Keys (BYOK)
Supply your own LLM API keys or point Architect at a self-hosted model endpoint (Llama, Mistral, or any OpenAI-compatible API). Credentials never leave your vault.
Private Data Source Connectors
Connect agents to internal PostgreSQL, MySQL, MongoDB, or vector databases without routing through any external service. All query execution is in-network.
Built-In Observability
Real-time agent activity monitoring, trace logging, and Prometheus-compatible metrics — all exported to your internal observability stack. No external dashboards required.
Air-Gap Compatible
Architect can operate in fully disconnected environments. Package and ship the runtime image to air-gapped networks for classified, defense, or highly regulated use cases.
No-Code Agent Builder
Non-engineers can configure, test, and publish AI agents through a visual interface — no Python, no YAML, no CLI. Your DevOps team handles the infra; your domain experts build the logic.
How It Works

Four Steps to a Private AI Agent

1
Deploy the Runtime
Pull the Architect Docker image or Helm chart. Deploy to your Kubernetes cluster, VM, or bare-metal server in minutes.
2
Connect Your Models & Data
Point Architect at your self-hosted LLM endpoint or supply API keys. Connect internal databases and APIs — all traffic stays on-prem.
3
Build Your Agent
Use the visual no-code builder to define your agent's persona, tools, memory, and workflows. No coding required for most configurations.
4
Go Live & Monitor
Publish your agent app. Observe activity in real time via your internal Prometheus/Grafana stack. Iterate without redeployment.
Before vs. After

What Changes When You Own Your AI

Without Architect
  • Sensitive data routed through third-party AI cloud APIs, creating compliance exposure
  • Weeks of custom engineering to wire AI into internal infrastructure securely
  • Unpredictable per-token SaaS costs that spike with usage at scale
  • No visibility into what data leaves your environment or how it is used by AI vendors
  • GDPR, HIPAA, and SOC 2 auditors flag AI usage as a residency risk
With Architect
  • All agent inference, memory, and tool calls execute within your own infrastructure perimeter
  • Production-ready private agent app running in under 10 minutes via Helm or Docker Compose
  • Flat, predictable infrastructure cost — no per-token SaaS fees at scale
  • Full audit trail, trace logs, and activity monitoring for GDPR, HIPAA, and SOC 2 compliance
  • Real-time observability into every agent action via Prometheus-compatible metrics endpoints
Agent Prompt

Sample Agent Configuration

A realistic system prompt for a private infrastructure AI agent deployed via Architect — ready to paste and customize.

architect-agent — private-infra-assistant.prompt
Private Mode — All execution on-premise — No external API calls 
You are a private AI assistant deployed entirely within [COMPANY]'s infrastructure.
You have access to internal tools and databases only. You MUST NOT call any external APIs
or transmit data outside the company network perimeter under any circumstances.

Your capabilities include:
- Query the internal PostgreSQL knowledge base via the `db_query` tool
- Search indexed internal documents via the `vector_search` tool
- Trigger approved internal workflows via the `workflow_dispatch` tool

Security constraints:
- Refuse any request that would require sending data to an external endpoint
- Log all tool invocations to the internal audit trail
- Apply role-based access: only surface data the requesting user is authorized to view

Always respond concisely. Cite the internal source document or DB record when applicable.
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FAQ

Common Questions

Can I deploy Architect AI agents on my own servers?
Yes. Architect supports fully self-hosted deployment on your own VMs, Kubernetes clusters, or bare-metal servers. No data ever leaves your infrastructure — the entire agent runtime, including memory and tool execution, operates within your network perimeter.
Does Architect support bring-your-own LLM?
Architect supports BYOK (Bring Your Own Keys) and BYOI (Bring Your Own Infrastructure), including self-hosted LLMs like Llama, Mistral, and any OpenAI-compatible endpoint such as LM Studio or vLLM. Your model credentials are stored in your own secrets manager.
How long does it take to deploy a private AI agent with Architect?
Architect is designed for rapid deployment. Most teams go from a clean Kubernetes namespace to a production-ready, fully private AI agent app in under 10 minutes using the provided Helm chart or Docker Compose file.
Is Architect compliant with data sovereignty and privacy regulations?
Because Architect runs entirely within your infrastructure perimeter with no external data transmission, it is inherently compatible with GDPR, HIPAA, SOC 2, and other data residency mandates. Full audit logging and trace exports are included for compliance evidence.
What infrastructure types does Architect support for private deployment?
Architect supports deployment on AWS, Azure, and GCP (private VPCs), on-premise bare metal, any CNCF-conformant Kubernetes distribution (EKS, AKS, GKE, K3s, RKE), and fully air-gapped environments for classified or high-security use cases.

Your Infrastructure. Your AI. Your Control.

Deploy a production-grade private AI agent app inside your own perimeter in under 10 minutes. No cloud lock-in. No data leaves your network.

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